For this problem, we are going to use reuters dataset. It is a set of short newswires along with their topics published by Reuters in 1986. It is a simple, widely used toy dastaset for text classification. You are going to use a simple feedforward neural network to classify reuters news into 46 different topics/classes. The reuters dataset comes packaged as part of Keras . Import the dataset from keras using the following commands:
library(keras)
reuters = dataset_reuters(num_words=10000)
Take a look at the structure of reuters.dataset. The dataset is already pre-processed and split into train and test sets. Each example in the train or test set represents a news article and is stored as a list of integers where each integer represents the index of a specific word appearing in that article. When you set num_words=1000 in dataset_reuters, then keras keeps only the top 10000 most frequent words in the data. Let’s take a look at the structure of the training examples:
str(reuters$train$x)
List of 8982
$ : int [1:87] 1 2 2 8 43 10 447 5 25 207 ...
$ : int [1:56] 1 3267 699 3434 2295 56 2 7511 9 56 ...
$ : int [1:139] 1 53 12 284 15 14 272 26 53 959 ...
$ : int [1:224] 1 4 686 867 558 4 37 38 309 2276 ...
$ : int [1:101] 1 8295 111 8 25 166 40 638 10 436 ...
$ : int [1:116] 1 4 37 38 309 213 349 1632 48 193 ...
$ : int [1:100] 1 56 5539 925 149 8 16 23 931 3875 ...
$ : int [1:100] 1 53 648 26 14 749 26 39 6207 5466 ...
$ : int [1:82] 1 178 53 321 26 14 948 26 178 39 ...
$ : int [1:106] 1 56 7224 81 40 1175 174 2 6 1793 ...
$ : int [1:31] 1 245 273 207 156 53 74 160 26 14 ...
$ : int [1:59] 1 56 141 5618 1607 149 8 16 33 223 ...
$ : int [1:65] 1 2 81 8 16 625 42 120 7 1679 ...
$ : int [1:316] 1 248 409 166 1461 1284 3906 8 4 495 ...
$ : int [1:527] 1 4 113 23 133 6 433 226 7 1182 ...
$ : int [1:76] 1 577 9 355 430 21 4 2222 5 4 ...
$ : int [1:114] 1 945 65 111 8 10 498 40 85 2120 ...
$ : int [1:17] 1 486 341 785 26 14 482 26 255 606 ...
$ : int [1:91] 1 53 19 296 15 14 258 26 53 959 ...
$ : int [1:77] 1 7567 851 260 542 159 13 52 29 23 ...
$ : int [1:231] 1 779 37 38 465 278 6623 55 900 6 ...
$ : int [1:108] 1 73 418 904 2627 2198 8 36 717 271 ...
$ : int [1:83] 1 2 71 8 16 385 6 42 904 103 ...
$ : int [1:29] 1 245 273 397 124 53 191 26 14 83 ...
$ : int [1:95] 1 29 6 207 156 169 103 858 131 74 ...
$ : int [1:110] 1 144 62 2115 451 82 5 37 38 399 ...
$ : int [1:23] 1 53 745 26 14 722 26 39 7442 18 ...
$ : int [1:373] 1 10 545 856 3931 1187 2 33 1076 2045 ...
$ : int [1:114] 1 178 53 279 26 14 124 26 178 39 ...
$ : int [1:354] 1 2163 317 65 131 1462 23 768 1225 2 ...
$ : int [1:133] 1 4 37 38 309 213 8 443 37 38 ...
$ : int [1:222] 1 293 270 111 8 16 34 4814 27 3546 ...
$ : int [1:571] 1 4 37 38 424 309 415 524 795 6 ...
$ : int [1:155] 1 4 1795 232 60 240 128 140 21 68 ...
$ : int [1:83] 1 4 37 38 23 6 3186 6526 841 11 ...
$ : int [1:208] 1 1961 81 149 56 2 115 8 16 33 ...
$ : int [1:170] 1 1378 234 99 610 60 8 4 60 1543 ...
$ : int [1:269] 1 978 66 262 1251 2 8 107 4 293 ...
$ : int [1:74] 1 29 6 94 156 89 67 2115 2453 14 ...
$ : int [1:19] 1 486 341 119 26 14 119 26 7 255 ...
$ : int [1:23] 1 53 258 26 14 187 26 39 3914 18 ...
$ : int [1:78] 1 4 7085 66 253 2776 6 5345 11 15 ...
$ : int [1:21] 1 599 1815 299 45 1320 194 198 2041 28 ...
$ : int [1:377] 1 496 427 111 450 91 57 6 679 25 ...
$ : int [1:104] 1 2856 56 2 626 450 8 16 40 129 ...
$ : int [1:299] 1 4 37 38 431 8 25 1213 1957 5 ...
$ : int [1:89] 1 2 442 101 13 104 34 68 20 217 ...
$ : int [1:56] 1 155 822 62 3510 9 188 5104 7 42 ...
$ : int [1:94] 1 60 5 130 1461 3366 1896 8 36 2464 ...
$ : int [1:139] 1 53 284 26 14 319 39 47 5211 18 ...
$ : int [1:118] 1 1479 1197 71 8 25 1479 1197 640 71 ...
$ : int [1:36] 1 53 19 1090 15 14 1018 26 39 44 ...
$ : int [1:137] 1 2185 921 9 1493 103 4971 1925 8 16 ...
$ : int [1:107] 1 53 74 312 26 14 651 10 39 74 ...
$ : int [1:83] 1 537 232 1231 537 232 703 111 8 16 ...
$ : int [1:66] 1 53 191 26 14 158 26 39 19 3412 ...
$ : int [1:70] 1 53 46 142 26 14 46 155 26 39 ...
$ : int [1:112] 1 7674 2 71 8 16 2892 3514 1620 2357 ...
$ : int [1:88] 1 2626 141 450 56 2626 626 8 16 64 ...
$ : int [1:51] 1 53 767 26 14 124 26 39 72 2756 ...
$ : int [1:83] 1 56 735 268 626 71 8 16 41 2049 ...
$ : int [1:123] 1 2 231 81 8 16 638 42 3699 322 ...
$ : int [1:17] 1 486 341 312 26 14 312 26 255 219 ...
$ : int [1:185] 1 1537 9347 534 45 6 761 13 10 393 ...
$ : int [1:84] 1 1284 5682 136 484 5 789 8 54 2395 ...
$ : int [1:52] 1 218 430 21 4 2222 5 181 37 38 ...
$ : int [1:102] 1 56 5539 925 149 8 25 116 13 12 ...
$ : int [1:73] 1 2 752 13 234 867 247 79 8 16 ...
$ : int [1:106] 1 56 1621 3922 9 1229 81 5662 369 25 ...
$ : int [1:486] 1 367 40 2575 1470 6 30 7 538 5 ...
$ : int [1:107] 1 2 691 149 8 2 600 822 28 25 ...
$ : int [1:82] 1 53 751 26 14 648 26 39 482 32 ...
$ : int [1:263] 1 802 64 10 4478 66 253 5 32 59 ...
$ : int [1:172] 1 6475 214 71 8 25 362 23 7326 6 ...
$ : int [1:491] 1 569 40 129 306 572 13 25 357 162 ...
$ : int [1:190] 1 5985 2861 282 5 2883 9037 28 153 48 ...
$ : int [1:143] 1 2173 3174 2841 491 8 2478 3638 2383 3096 ...
$ : int [1:62] 1 4 294 259 1613 16 3308 4 198 5 ...
$ : int [1:26] 1 4 497 81 8 4 354 598 846 1227 ...
$ : int [1:88] 1 2 111 8 56 9891 2 5 2 192 ...
$ : int [1:114] 1 1139 357 162 114 513 6 258 11 1232 ...
$ : int [1:38] 1 53 272 26 14 158 26 39 32 3125 ...
$ : int [1:85] 1 53 284 26 14 684 26 39 19 7103 ...
$ : int [1:112] 1 4 37 38 740 291 1098 1641 40 1175 ...
$ : int [1:793] 1 37 412 128 140 1431 306 6 449 246 ...
$ : int [1:104] 1 178 53 46 142 26 14 46 319 2 ...
$ : int [1:25] 1 53 321 26 14 614 26 39 19 3611 ...
$ : int [1:21] 1 486 341 61 19 32 26 14 61 19 ...
$ : int [1:101] 1 56 1100 392 149 785 20 324 27 1406 ...
$ : int [1:28] 1 53 684 26 14 648 26 39 19 1746 ...
$ : int [1:25] 1 2 1568 81 8 25 166 887 10 142 ...
$ : int [1:81] 1 8521 81 384 4 8962 1029 111 8 16 ...
$ : int [1:135] 1 53 750 26 14 644 26 39 758 980 ...
$ : int [1:73] 1 56 234 1829 81 8 16 40 471 10 ...
$ : int [1:62] 1 6120 23 772 6 334 93 187 13 10 ...
$ : int [1:18] 1 486 341 158 44 26 14 158 44 26 ...
$ : int [1:90] 1 4 237 259 1064 137 1386 13 664 76 ...
$ : int [1:266] 1 4263 2162 81 8 24 25 731 1092 5 ...
$ : int [1:91] 1 4 248 409 23 133 6 2156 4 106 ...
[list output truncated]
This means that the first article consists of the words with indices 1,2,2,8,etc. As you can see, the examples in the train and test data are vectors of varying lengths. Neural Networks requires a matrix where each row represents an example and each column represent an attribute of that example. Therefore, to prepare this data for neural networks we need to make sure that all examples have the same number of columns ( that is, they are vectors of the same length). To do this, we do one- hot encoding of each example to turn them into vectors of 0s and 1s. This would mean for instance, turning the sequence [1,2,2,8,….] into a 10000 dimensional vector that would be all zeros except for indices 1,2,8, etc. In other words, we turn each news article into a 10000 dimensional binary vector which indicates which of the top 10000 frequent words occur in that article. You can use the following r function to do this one-hot-encoding:
one_hot_encoding = function(x, dimension=10000) {
encoded = matrix(0, length(x), dimension)
for (i in 1:length(x))
encoded[i, x[[i]]] = 1
encoded
}
Where x is the list of examples for which you want to do one-hot-encoding. Call this function on reuters$train$x and reuters$test$x to get the one-hot encoding of the train and test examples. This will produce a matrix with dimensions (8982,10000) for the train data and a matrix with dimensions(2246, 10000) for the test data. You can now use these matrices to train and test your neural network model.
reuters_train = one_hot_encoding(reuters$train$x)
reuters_test = one_hot_encoding(reuters$test$x)
Q1. (5 pts) Create an ANN model to classify reuters news article into 46 classes (note that reuters$train$y and reuters$test$y are vectors of integers between 0-45 representing the category of each news article). Use at least two hidden layers and compute the accuracy of your model on the test set. Unlike the fashion Mnist dataset where each image had to be flattened into a one dimensional vector, for the reuters dataset, you do not need the flatten layer before the dense layer as each observation (news article) is already one dimensional.
model <- keras_model_sequential()
model %>%
layer_dense( units = 50, activation = "relu", input_shape = 10000) %>%
layer_dense( units = 50, activation = "relu") %>%
layer_dense( units = 50, activation = "relu") %>%
layer_dense(units = 46, activation = 'softmax')
set.seed(123)
model %>% compile (
loss = 'sparse_categorical_crossentropy',
optimizer = 'adam',
metrics = 'accuracy')
history = model %>% fit (x = reuters_train, y = reuters$train$y)
Epoch 1/10
1/281 [..............................] - ETA: 0s - loss: 3.8340 - accuracy: 0.0000e+00
25/281 [=>............................] - ETA: 0s - loss: 3.3145 - accuracy: 0.3363
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281/281 [==============================] - 1s 2ms/step - loss: 1.5719 - accuracy: 0.6436
281/281 [==============================] - 1s 4ms/step - loss: 1.5719 - accuracy: 0.6436
Epoch 2/10
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281/281 [==============================] - 1s 2ms/step - loss: 0.7536 - accuracy: 0.8250
281/281 [==============================] - 1s 3ms/step - loss: 0.7536 - accuracy: 0.8250
Epoch 3/10
1/281 [..............................] - ETA: 0s - loss: 0.5418 - accuracy: 0.8438
26/281 [=>............................] - ETA: 0s - loss: 0.4354 - accuracy: 0.9087
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188/281 [===================>..........] - ETA: 0s - loss: 0.4017 - accuracy: 0.9109
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235/281 [========================>.....] - ETA: 0s - loss: 0.4000 - accuracy: 0.9128
259/281 [==========================>...] - ETA: 0s - loss: 0.4006 - accuracy: 0.9122
281/281 [==============================] - 1s 2ms/step - loss: 0.4045 - accuracy: 0.9103
281/281 [==============================] - 1s 3ms/step - loss: 0.4045 - accuracy: 0.9103
Epoch 4/10
1/281 [..............................] - ETA: 0s - loss: 0.3514 - accuracy: 0.9375
24/281 [=>............................] - ETA: 0s - loss: 0.1977 - accuracy: 0.9557
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269/281 [===========================>..] - ETA: 0s - loss: 0.2626 - accuracy: 0.9405
281/281 [==============================] - 1s 3ms/step - loss: 0.2622 - accuracy: 0.9403
281/281 [==============================] - 1s 4ms/step - loss: 0.2622 - accuracy: 0.9403
Epoch 5/10
1/281 [..............................] - ETA: 0s - loss: 0.1405 - accuracy: 0.9688
24/281 [=>............................] - ETA: 0s - loss: 0.1425 - accuracy: 0.9661
46/281 [===>..........................] - ETA: 0s - loss: 0.1706 - accuracy: 0.9558
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279/281 [============================>.] - ETA: 0s - loss: 0.1951 - accuracy: 0.9476
281/281 [==============================] - 1s 2ms/step - loss: 0.1956 - accuracy: 0.9475
281/281 [==============================] - 1s 3ms/step - loss: 0.1956 - accuracy: 0.9475
Epoch 6/10
1/281 [..............................] - ETA: 0s - loss: 0.0362 - accuracy: 1.0000
23/281 [=>............................] - ETA: 0s - loss: 0.1524 - accuracy: 0.9552
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281/281 [==============================] - 1s 2ms/step - loss: 0.1733 - accuracy: 0.9505
281/281 [==============================] - 1s 3ms/step - loss: 0.1733 - accuracy: 0.9505
Epoch 7/10
1/281 [..............................] - ETA: 0s - loss: 0.3076 - accuracy: 0.9062
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281/281 [==============================] - 1s 2ms/step - loss: 0.1526 - accuracy: 0.9516
281/281 [==============================] - 1s 3ms/step - loss: 0.1526 - accuracy: 0.9516
Epoch 8/10
1/281 [..............................] - ETA: 0s - loss: 0.0567 - accuracy: 0.9688
25/281 [=>............................] - ETA: 0s - loss: 0.0973 - accuracy: 0.9625
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281/281 [==============================] - 1s 2ms/step - loss: 0.1417 - accuracy: 0.9501
281/281 [==============================] - 1s 3ms/step - loss: 0.1417 - accuracy: 0.9501
Epoch 9/10
1/281 [..............................] - ETA: 0s - loss: 0.0837 - accuracy: 0.9375
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281/281 [==============================] - 1s 2ms/step - loss: 0.1309 - accuracy: 0.9516
281/281 [==============================] - 1s 3ms/step - loss: 0.1309 - accuracy: 0.9516
Epoch 10/10
1/281 [..............................] - ETA: 0s - loss: 0.0455 - accuracy: 1.0000
23/281 [=>............................] - ETA: 0s - loss: 0.0943 - accuracy: 0.9647
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281/281 [==============================] - 1s 2ms/step - loss: 0.1242 - accuracy: 0.9532
281/281 [==============================] - 1s 3ms/step - loss: 0.1242 - accuracy: 0.9532
score <- model %>% evaluate(reuters_test, reuters$test$y, verbose = 2)
71/71 - 0s - loss: 1.1694 - accuracy: 0.7930
71/71 - 0s - loss: 1.1694 - accuracy: 0.7930
cat('Test accuracy:', score[2], "\n")
Test accuracy: 0.7929653
Q2. (5 pts) Split the train data into train/validation set. Use the first 1000 examples in reuters$train for validation and the rest for training your model. Use “tfruns” package to tune your ANN’s hyperparameters including, the number of nodes in each hidden layer, the activation function in each hidden layer, batch_size, learning_rate, and the number of epochs). Validate each model on the validation set.
Answer the following questions:
1- Which model ( which hyper-parameter combination) resulted in the best accuracy on the validation data? Make sure that you print the returned value from tfruns and report the
run with the highest validation accuracy.
2- Print the learning curve of your best model. Does your best model still overfit?
3- Does your validation_loss stop decreasing after several epochs? If so, at roughly which epoch
does your validation_loss stop decreasing?
reuters_validation_x = one_hot_encoding(reuters$train$x[1:1000])
validation_labels = reuters$train$y[1:1000]
reuters_train = one_hot_encoding(reuters$train$x[1001:length(reuters$train$x)])
reuters_train_labels = reuters$train$y[1001:length(reuters$train$y)]
library(tfruns)
runs <- tuning_run("reuters.R",
flags = list (
nodes = c(64, 128, 392),
learning_rate = c(0.01, 0.05, 0.001, 0.0001),
batch_size = c(100, 200, 500, 1000),
epochs = c(30,50,100),
activation = c("relu","sigmoid","tanh")
), sample = 0.02)
432 total combinations of flags (sampled to 8 combinations)
Y
Training run 1/8 (flags = list(64, 0.001, 500, 100, "tanh"))
Using run directory runs/2020-11-02T21-15-38Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/100
1/16 [>.............................] - ETA: 0s - loss: 3.8445 - accuracy: 0.0060
6/16 [==========>...................] - ETA: 0s - loss: 3.4640 - accuracy: 0.3697
11/16 [===================>..........] - ETA: 0s - loss: 3.1090 - accuracy: 0.4420
16/16 [==============================] - 0s 11ms/step - loss: 2.8393 - accuracy: 0.4698
16/16 [==============================] - 1s 51ms/step - loss: 2.8393 - accuracy: 0.4698 - val_loss: 2.0065 - val_accuracy: 0.5380
Epoch 2/100
1/16 [>.............................] - ETA: 0s - loss: 1.9950 - accuracy: 0.5400
4/16 [======>.......................] - ETA: 0s - loss: 1.8731 - accuracy: 0.5530
8/16 [==============>...............] - ETA: 0s - loss: 1.8033 - accuracy: 0.5748
11/16 [===================>..........] - ETA: 0s - loss: 1.7474 - accuracy: 0.5991
13/16 [=======================>......] - ETA: 0s - loss: 1.7114 - accuracy: 0.6105
16/16 [==============================] - 0s 18ms/step - loss: 1.6671 - accuracy: 0.6262
16/16 [==============================] - 0s 28ms/step - loss: 1.6671 - accuracy: 0.6262 - val_loss: 1.4758 - val_accuracy: 0.6710
Epoch 3/100
1/16 [>.............................] - ETA: 0s - loss: 1.3516 - accuracy: 0.7140
5/16 [========>.....................] - ETA: 0s - loss: 1.3834 - accuracy: 0.7024
9/16 [===============>..............] - ETA: 0s - loss: 1.2944 - accuracy: 0.7156
14/16 [=========================>....] - ETA: 0s - loss: 1.2335 - accuracy: 0.7294
16/16 [==============================] - 0s 12ms/step - loss: 1.2155 - accuracy: 0.7347
16/16 [==============================] - 0s 22ms/step - loss: 1.2155 - accuracy: 0.7347 - val_loss: 1.1956 - val_accuracy: 0.7310
Epoch 4/100
1/16 [>.............................] - ETA: 0s - loss: 0.9878 - accuracy: 0.7920
5/16 [========>.....................] - ETA: 0s - loss: 0.9635 - accuracy: 0.8072
9/16 [===============>..............] - ETA: 0s - loss: 0.9439 - accuracy: 0.8107
13/16 [=======================>......] - ETA: 0s - loss: 0.9404 - accuracy: 0.8118
16/16 [==============================] - 0s 12ms/step - loss: 0.9229 - accuracy: 0.8141
16/16 [==============================] - 0s 22ms/step - loss: 0.9229 - accuracy: 0.8141 - val_loss: 1.0460 - val_accuracy: 0.7730
Epoch 5/100
1/16 [>.............................] - ETA: 0s - loss: 0.7693 - accuracy: 0.8500
5/16 [========>.....................] - ETA: 0s - loss: 0.7980 - accuracy: 0.8480
9/16 [===============>..............] - ETA: 0s - loss: 0.7623 - accuracy: 0.8553
14/16 [=========================>....] - ETA: 0s - loss: 0.7267 - accuracy: 0.8621
16/16 [==============================] - 0s 12ms/step - loss: 0.7137 - accuracy: 0.8639
16/16 [==============================] - 0s 22ms/step - loss: 0.7137 - accuracy: 0.8639 - val_loss: 0.9601 - val_accuracy: 0.7970
Epoch 6/100
1/16 [>.............................] - ETA: 0s - loss: 0.5656 - accuracy: 0.9140
5/16 [========>.....................] - ETA: 0s - loss: 0.6039 - accuracy: 0.8908
9/16 [===============>..............] - ETA: 0s - loss: 0.5681 - accuracy: 0.8947
13/16 [=======================>......] - ETA: 0s - loss: 0.5613 - accuracy: 0.8949
16/16 [==============================] - 0s 13ms/step - loss: 0.5575 - accuracy: 0.8954
16/16 [==============================] - 0s 22ms/step - loss: 0.5575 - accuracy: 0.8954 - val_loss: 0.9083 - val_accuracy: 0.8030
Epoch 7/100
1/16 [>.............................] - ETA: 0s - loss: 0.4370 - accuracy: 0.9260
6/16 [==========>...................] - ETA: 0s - loss: 0.4682 - accuracy: 0.9157
11/16 [===================>..........] - ETA: 0s - loss: 0.4628 - accuracy: 0.9151
16/16 [==============================] - 0s 11ms/step - loss: 0.4412 - accuracy: 0.9193
16/16 [==============================] - 0s 21ms/step - loss: 0.4412 - accuracy: 0.9193 - val_loss: 0.8801 - val_accuracy: 0.8070
Epoch 8/100
1/16 [>.............................] - ETA: 0s - loss: 0.3575 - accuracy: 0.9440
5/16 [========>.....................] - ETA: 0s - loss: 0.3471 - accuracy: 0.9440
9/16 [===============>..............] - ETA: 0s - loss: 0.3453 - accuracy: 0.9431
13/16 [=======================>......] - ETA: 0s - loss: 0.3583 - accuracy: 0.9365
16/16 [==============================] - 0s 12ms/step - loss: 0.3573 - accuracy: 0.9361
16/16 [==============================] - 0s 22ms/step - loss: 0.3573 - accuracy: 0.9361 - val_loss: 0.8737 - val_accuracy: 0.8080
Epoch 9/100
1/16 [>.............................] - ETA: 0s - loss: 0.3376 - accuracy: 0.9500
6/16 [==========>...................] - ETA: 0s - loss: 0.2974 - accuracy: 0.9503
10/16 [=================>............] - ETA: 0s - loss: 0.2956 - accuracy: 0.9474
15/16 [===========================>..] - ETA: 0s - loss: 0.2974 - accuracy: 0.9451
16/16 [==============================] - 0s 12ms/step - loss: 0.2967 - accuracy: 0.9445
16/16 [==============================] - 0s 21ms/step - loss: 0.2967 - accuracy: 0.9445 - val_loss: 0.8843 - val_accuracy: 0.8060
Epoch 10/100
1/16 [>.............................] - ETA: 0s - loss: 0.2757 - accuracy: 0.9500
5/16 [========>.....................] - ETA: 0s - loss: 0.2432 - accuracy: 0.9556
9/16 [===============>..............] - ETA: 0s - loss: 0.2381 - accuracy: 0.9569
13/16 [=======================>......] - ETA: 0s - loss: 0.2432 - accuracy: 0.9548
16/16 [==============================] - 0s 13ms/step - loss: 0.2497 - accuracy: 0.9515
16/16 [==============================] - 0s 22ms/step - loss: 0.2497 - accuracy: 0.9515 - val_loss: 0.8675 - val_accuracy: 0.8120
Epoch 11/100
1/16 [>.............................] - ETA: 0s - loss: 0.2338 - accuracy: 0.9600
5/16 [========>.....................] - ETA: 0s - loss: 0.1949 - accuracy: 0.9608
9/16 [===============>..............] - ETA: 0s - loss: 0.2028 - accuracy: 0.9591
13/16 [=======================>......] - ETA: 0s - loss: 0.2087 - accuracy: 0.9558
16/16 [==============================] - 0s 13ms/step - loss: 0.2118 - accuracy: 0.9536
16/16 [==============================] - 0s 23ms/step - loss: 0.2118 - accuracy: 0.9536 - val_loss: 0.8655 - val_accuracy: 0.8130
Epoch 12/100
1/16 [>.............................] - ETA: 0s - loss: 0.1506 - accuracy: 0.9760
5/16 [========>.....................] - ETA: 0s - loss: 0.1692 - accuracy: 0.9680
9/16 [===============>..............] - ETA: 0s - loss: 0.1733 - accuracy: 0.9633
13/16 [=======================>......] - ETA: 0s - loss: 0.1812 - accuracy: 0.9580
16/16 [==============================] - 0s 13ms/step - loss: 0.1826 - accuracy: 0.9574
16/16 [==============================] - 0s 22ms/step - loss: 0.1826 - accuracy: 0.9574 - val_loss: 0.8829 - val_accuracy: 0.8080
Epoch 13/100
1/16 [>.............................] - ETA: 0s - loss: 0.1555 - accuracy: 0.9620
5/16 [========>.....................] - ETA: 0s - loss: 0.1555 - accuracy: 0.9660
9/16 [===============>..............] - ETA: 0s - loss: 0.1524 - accuracy: 0.9638
13/16 [=======================>......] - ETA: 0s - loss: 0.1560 - accuracy: 0.9594
16/16 [==============================] - 0s 12ms/step - loss: 0.1602 - accuracy: 0.9572
16/16 [==============================] - 0s 22ms/step - loss: 0.1602 - accuracy: 0.9572 - val_loss: 0.8812 - val_accuracy: 0.8090
Epoch 14/100
1/16 [>.............................] - ETA: 0s - loss: 0.1323 - accuracy: 0.9660
5/16 [========>.....................] - ETA: 0s - loss: 0.1298 - accuracy: 0.9672
9/16 [===============>..............] - ETA: 0s - loss: 0.1410 - accuracy: 0.9620
13/16 [=======================>......] - ETA: 0s - loss: 0.1436 - accuracy: 0.9592
16/16 [==============================] - 0s 13ms/step - loss: 0.1430 - accuracy: 0.9597
16/16 [==============================] - 0s 22ms/step - loss: 0.1430 - accuracy: 0.9597 - val_loss: 0.8901 - val_accuracy: 0.8080
Epoch 15/100
1/16 [>.............................] - ETA: 0s - loss: 0.1272 - accuracy: 0.9620
5/16 [========>.....................] - ETA: 0s - loss: 0.1185 - accuracy: 0.9688
9/16 [===============>..............] - ETA: 0s - loss: 0.1199 - accuracy: 0.9667
13/16 [=======================>......] - ETA: 0s - loss: 0.1287 - accuracy: 0.9620
16/16 [==============================] - 0s 12ms/step - loss: 0.1298 - accuracy: 0.9603
16/16 [==============================] - 0s 22ms/step - loss: 0.1298 - accuracy: 0.9603 - val_loss: 0.9011 - val_accuracy: 0.8080
Epoch 16/100
1/16 [>.............................] - ETA: 0s - loss: 0.0959 - accuracy: 0.9840
5/16 [========>.....................] - ETA: 0s - loss: 0.1203 - accuracy: 0.9656
9/16 [===============>..............] - ETA: 0s - loss: 0.1179 - accuracy: 0.9631
13/16 [=======================>......] - ETA: 0s - loss: 0.1203 - accuracy: 0.9602
16/16 [==============================] - 0s 13ms/step - loss: 0.1195 - accuracy: 0.9595
16/16 [==============================] - 0s 23ms/step - loss: 0.1195 - accuracy: 0.9595 - val_loss: 0.9033 - val_accuracy: 0.8060
Epoch 17/100
1/16 [>.............................] - ETA: 0s - loss: 0.0974 - accuracy: 0.9680
5/16 [========>.....................] - ETA: 0s - loss: 0.1029 - accuracy: 0.9676
9/16 [===============>..............] - ETA: 0s - loss: 0.1089 - accuracy: 0.9644
13/16 [=======================>......] - ETA: 0s - loss: 0.1094 - accuracy: 0.9612
16/16 [==============================] - 0s 13ms/step - loss: 0.1120 - accuracy: 0.9599
16/16 [==============================] - 0s 22ms/step - loss: 0.1120 - accuracy: 0.9599 - val_loss: 0.9163 - val_accuracy: 0.8080
Epoch 18/100
1/16 [>.............................] - ETA: 0s - loss: 0.1037 - accuracy: 0.9720
5/16 [========>.....................] - ETA: 0s - loss: 0.0921 - accuracy: 0.9728
9/16 [===============>..............] - ETA: 0s - loss: 0.0968 - accuracy: 0.9676
13/16 [=======================>......] - ETA: 0s - loss: 0.0998 - accuracy: 0.9635
16/16 [==============================] - 0s 12ms/step - loss: 0.1063 - accuracy: 0.9600
16/16 [==============================] - 0s 22ms/step - loss: 0.1063 - accuracy: 0.9600 - val_loss: 0.9151 - val_accuracy: 0.8080
Epoch 19/100
1/16 [>.............................] - ETA: 0s - loss: 0.0964 - accuracy: 0.9680
5/16 [========>.....................] - ETA: 0s - loss: 0.0915 - accuracy: 0.9672
10/16 [=================>............] - ETA: 0s - loss: 0.0967 - accuracy: 0.9636
14/16 [=========================>....] - ETA: 0s - loss: 0.0991 - accuracy: 0.9616
16/16 [==============================] - 0s 12ms/step - loss: 0.0990 - accuracy: 0.9609
16/16 [==============================] - 0s 22ms/step - loss: 0.0990 - accuracy: 0.9609 - val_loss: 0.9278 - val_accuracy: 0.8080
Epoch 20/100
1/16 [>.............................] - ETA: 0s - loss: 0.0839 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0890 - accuracy: 0.9663
11/16 [===================>..........] - ETA: 0s - loss: 0.0914 - accuracy: 0.9651
15/16 [===========================>..] - ETA: 0s - loss: 0.0961 - accuracy: 0.9607
16/16 [==============================] - 0s 12ms/step - loss: 0.0961 - accuracy: 0.9605
16/16 [==============================] - 0s 21ms/step - loss: 0.0961 - accuracy: 0.9605 - val_loss: 0.9232 - val_accuracy: 0.8020
Epoch 21/100
1/16 [>.............................] - ETA: 0s - loss: 0.1001 - accuracy: 0.9560
6/16 [==========>...................] - ETA: 0s - loss: 0.0847 - accuracy: 0.9670
11/16 [===================>..........] - ETA: 0s - loss: 0.0866 - accuracy: 0.9651
16/16 [==============================] - 0s 11ms/step - loss: 0.0926 - accuracy: 0.9608
16/16 [==============================] - 0s 21ms/step - loss: 0.0926 - accuracy: 0.9608 - val_loss: 0.9401 - val_accuracy: 0.8070
Epoch 22/100
1/16 [>.............................] - ETA: 0s - loss: 0.0823 - accuracy: 0.9660
5/16 [========>.....................] - ETA: 0s - loss: 0.0849 - accuracy: 0.9688
9/16 [===============>..............] - ETA: 0s - loss: 0.0824 - accuracy: 0.9671
13/16 [=======================>......] - ETA: 0s - loss: 0.0828 - accuracy: 0.9655
16/16 [==============================] - 0s 12ms/step - loss: 0.0875 - accuracy: 0.9625
16/16 [==============================] - 0s 22ms/step - loss: 0.0875 - accuracy: 0.9625 - val_loss: 0.9504 - val_accuracy: 0.8040
Epoch 23/100
1/16 [>.............................] - ETA: 0s - loss: 0.0684 - accuracy: 0.9780
6/16 [==========>...................] - ETA: 0s - loss: 0.0796 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0816 - accuracy: 0.9644
15/16 [===========================>..] - ETA: 0s - loss: 0.0826 - accuracy: 0.9623
16/16 [==============================] - 0s 11ms/step - loss: 0.0833 - accuracy: 0.9618
16/16 [==============================] - 0s 21ms/step - loss: 0.0833 - accuracy: 0.9618 - val_loss: 0.9500 - val_accuracy: 0.8040
Epoch 24/100
1/16 [>.............................] - ETA: 0s - loss: 0.0728 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0855 - accuracy: 0.9627
11/16 [===================>..........] - ETA: 0s - loss: 0.0844 - accuracy: 0.9605
15/16 [===========================>..] - ETA: 0s - loss: 0.0830 - accuracy: 0.9609
16/16 [==============================] - 0s 12ms/step - loss: 0.0829 - accuracy: 0.9608
16/16 [==============================] - 0s 21ms/step - loss: 0.0829 - accuracy: 0.9608 - val_loss: 0.9573 - val_accuracy: 0.8070
Epoch 25/100
1/16 [>.............................] - ETA: 0s - loss: 0.0833 - accuracy: 0.9540
6/16 [==========>...................] - ETA: 0s - loss: 0.0703 - accuracy: 0.9653
11/16 [===================>..........] - ETA: 0s - loss: 0.0730 - accuracy: 0.9624
16/16 [==============================] - 0s 11ms/step - loss: 0.0804 - accuracy: 0.9573
16/16 [==============================] - 0s 21ms/step - loss: 0.0804 - accuracy: 0.9573 - val_loss: 0.9603 - val_accuracy: 0.8060
Epoch 26/100
1/16 [>.............................] - ETA: 0s - loss: 0.0816 - accuracy: 0.9560
6/16 [==========>...................] - ETA: 0s - loss: 0.0719 - accuracy: 0.9633
10/16 [=================>............] - ETA: 0s - loss: 0.0737 - accuracy: 0.9634
15/16 [===========================>..] - ETA: 0s - loss: 0.0785 - accuracy: 0.9612
16/16 [==============================] - 0s 12ms/step - loss: 0.0797 - accuracy: 0.9603
16/16 [==============================] - 0s 21ms/step - loss: 0.0797 - accuracy: 0.9603 - val_loss: 0.9586 - val_accuracy: 0.8050
Epoch 27/100
1/16 [>.............................] - ETA: 0s - loss: 0.0735 - accuracy: 0.9620
5/16 [========>.....................] - ETA: 0s - loss: 0.0793 - accuracy: 0.9596
10/16 [=================>............] - ETA: 0s - loss: 0.0742 - accuracy: 0.9616
15/16 [===========================>..] - ETA: 0s - loss: 0.0769 - accuracy: 0.9593
16/16 [==============================] - 0s 11ms/step - loss: 0.0777 - accuracy: 0.9587
16/16 [==============================] - 0s 21ms/step - loss: 0.0777 - accuracy: 0.9587 - val_loss: 0.9713 - val_accuracy: 0.8040
Epoch 28/100
1/16 [>.............................] - ETA: 0s - loss: 0.0672 - accuracy: 0.9680
5/16 [========>.....................] - ETA: 0s - loss: 0.0669 - accuracy: 0.9724
9/16 [===============>..............] - ETA: 0s - loss: 0.0684 - accuracy: 0.9693
14/16 [=========================>....] - ETA: 0s - loss: 0.0744 - accuracy: 0.9631
16/16 [==============================] - 0s 11ms/step - loss: 0.0759 - accuracy: 0.9622
16/16 [==============================] - 0s 21ms/step - loss: 0.0759 - accuracy: 0.9622 - val_loss: 0.9749 - val_accuracy: 0.8040
Epoch 29/100
1/16 [>.............................] - ETA: 0s - loss: 0.0593 - accuracy: 0.9720
5/16 [========>.....................] - ETA: 0s - loss: 0.0581 - accuracy: 0.9712
10/16 [=================>............] - ETA: 0s - loss: 0.0650 - accuracy: 0.9674
15/16 [===========================>..] - ETA: 0s - loss: 0.0731 - accuracy: 0.9609
16/16 [==============================] - 0s 11ms/step - loss: 0.0739 - accuracy: 0.9599
16/16 [==============================] - 0s 21ms/step - loss: 0.0739 - accuracy: 0.9599 - val_loss: 0.9791 - val_accuracy: 0.8120
Epoch 30/100
1/16 [>.............................] - ETA: 0s - loss: 0.0643 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0691 - accuracy: 0.9650
11/16 [===================>..........] - ETA: 0s - loss: 0.0700 - accuracy: 0.9627
15/16 [===========================>..] - ETA: 0s - loss: 0.0735 - accuracy: 0.9591
16/16 [==============================] - 0s 12ms/step - loss: 0.0734 - accuracy: 0.9589
16/16 [==============================] - 0s 21ms/step - loss: 0.0734 - accuracy: 0.9589 - val_loss: 0.9855 - val_accuracy: 0.8050
Epoch 31/100
1/16 [>.............................] - ETA: 0s - loss: 0.0729 - accuracy: 0.9600
5/16 [========>.....................] - ETA: 0s - loss: 0.0613 - accuracy: 0.9668
9/16 [===============>..............] - ETA: 0s - loss: 0.0679 - accuracy: 0.9624
13/16 [=======================>......] - ETA: 0s - loss: 0.0711 - accuracy: 0.9600
16/16 [==============================] - 0s 12ms/step - loss: 0.0717 - accuracy: 0.9592
16/16 [==============================] - 0s 21ms/step - loss: 0.0717 - accuracy: 0.9592 - val_loss: 0.9902 - val_accuracy: 0.8060
Epoch 32/100
1/16 [>.............................] - ETA: 0s - loss: 0.0563 - accuracy: 0.9700
6/16 [==========>...................] - ETA: 0s - loss: 0.0571 - accuracy: 0.9723
10/16 [=================>............] - ETA: 0s - loss: 0.0632 - accuracy: 0.9668
15/16 [===========================>..] - ETA: 0s - loss: 0.0683 - accuracy: 0.9616
16/16 [==============================] - 0s 12ms/step - loss: 0.0707 - accuracy: 0.9603
16/16 [==============================] - 0s 21ms/step - loss: 0.0707 - accuracy: 0.9603 - val_loss: 1.0030 - val_accuracy: 0.8020
Epoch 33/100
1/16 [>.............................] - ETA: 0s - loss: 0.0586 - accuracy: 0.9640
6/16 [==========>...................] - ETA: 0s - loss: 0.0627 - accuracy: 0.9687
10/16 [=================>............] - ETA: 0s - loss: 0.0656 - accuracy: 0.9644
15/16 [===========================>..] - ETA: 0s - loss: 0.0675 - accuracy: 0.9605
16/16 [==============================] - 0s 12ms/step - loss: 0.0684 - accuracy: 0.9594
16/16 [==============================] - 0s 21ms/step - loss: 0.0684 - accuracy: 0.9594 - val_loss: 0.9966 - val_accuracy: 0.8020
Epoch 34/100
1/16 [>.............................] - ETA: 0s - loss: 0.0739 - accuracy: 0.9600
6/16 [==========>...................] - ETA: 0s - loss: 0.0617 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0645 - accuracy: 0.9656
15/16 [===========================>..] - ETA: 0s - loss: 0.0676 - accuracy: 0.9624
16/16 [==============================] - 0s 12ms/step - loss: 0.0686 - accuracy: 0.9619
16/16 [==============================] - 0s 21ms/step - loss: 0.0686 - accuracy: 0.9619 - val_loss: 1.0207 - val_accuracy: 0.8030
Epoch 35/100
1/16 [>.............................] - ETA: 0s - loss: 0.0735 - accuracy: 0.9640
6/16 [==========>...................] - ETA: 0s - loss: 0.0605 - accuracy: 0.9707
10/16 [=================>............] - ETA: 0s - loss: 0.0661 - accuracy: 0.9650
14/16 [=========================>....] - ETA: 0s - loss: 0.0669 - accuracy: 0.9633
16/16 [==============================] - 0s 12ms/step - loss: 0.0678 - accuracy: 0.9628
16/16 [==============================] - 0s 21ms/step - loss: 0.0678 - accuracy: 0.9628 - val_loss: 1.0049 - val_accuracy: 0.8010
Epoch 36/100
1/16 [>.............................] - ETA: 0s - loss: 0.0507 - accuracy: 0.9780
6/16 [==========>...................] - ETA: 0s - loss: 0.0627 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0637 - accuracy: 0.9662
16/16 [==============================] - 0s 11ms/step - loss: 0.0681 - accuracy: 0.9620
16/16 [==============================] - 0s 21ms/step - loss: 0.0681 - accuracy: 0.9620 - val_loss: 1.0167 - val_accuracy: 0.8070
Epoch 37/100
1/16 [>.............................] - ETA: 0s - loss: 0.0420 - accuracy: 0.9800
5/16 [========>.....................] - ETA: 0s - loss: 0.0546 - accuracy: 0.9716
10/16 [=================>............] - ETA: 0s - loss: 0.0604 - accuracy: 0.9674
14/16 [=========================>....] - ETA: 0s - loss: 0.0635 - accuracy: 0.9644
16/16 [==============================] - 0s 12ms/step - loss: 0.0656 - accuracy: 0.9627
16/16 [==============================] - 0s 21ms/step - loss: 0.0656 - accuracy: 0.9627 - val_loss: 1.0299 - val_accuracy: 0.8000
Epoch 38/100
1/16 [>.............................] - ETA: 0s - loss: 0.0703 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0628 - accuracy: 0.9637
11/16 [===================>..........] - ETA: 0s - loss: 0.0634 - accuracy: 0.9622
16/16 [==============================] - 0s 11ms/step - loss: 0.0657 - accuracy: 0.9602
16/16 [==============================] - 0s 20ms/step - loss: 0.0657 - accuracy: 0.9602 - val_loss: 1.0121 - val_accuracy: 0.8090
Epoch 39/100
1/16 [>.............................] - ETA: 0s - loss: 0.0623 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0655 - accuracy: 0.9643
11/16 [===================>..........] - ETA: 0s - loss: 0.0585 - accuracy: 0.9662
15/16 [===========================>..] - ETA: 0s - loss: 0.0648 - accuracy: 0.9612
16/16 [==============================] - 0s 12ms/step - loss: 0.0648 - accuracy: 0.9612
16/16 [==============================] - 0s 21ms/step - loss: 0.0648 - accuracy: 0.9612 - val_loss: 1.0333 - val_accuracy: 0.8030
Epoch 40/100
1/16 [>.............................] - ETA: 0s - loss: 0.0585 - accuracy: 0.9660
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16/16 [==============================] - 0s 12ms/step - loss: 0.0644 - accuracy: 0.9608
16/16 [==============================] - 0s 21ms/step - loss: 0.0644 - accuracy: 0.9608 - val_loss: 1.0249 - val_accuracy: 0.8010
Epoch 41/100
1/16 [>.............................] - ETA: 0s - loss: 0.0592 - accuracy: 0.9720
5/16 [========>.....................] - ETA: 0s - loss: 0.0527 - accuracy: 0.9704
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16/16 [==============================] - 0s 12ms/step - loss: 0.0635 - accuracy: 0.9603
16/16 [==============================] - 0s 21ms/step - loss: 0.0635 - accuracy: 0.9603 - val_loss: 1.0421 - val_accuracy: 0.8040
Epoch 42/100
1/16 [>.............................] - ETA: 0s - loss: 0.0539 - accuracy: 0.9700
5/16 [========>.....................] - ETA: 0s - loss: 0.0568 - accuracy: 0.9696
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16/16 [==============================] - 0s 12ms/step - loss: 0.0623 - accuracy: 0.9615
16/16 [==============================] - 0s 21ms/step - loss: 0.0623 - accuracy: 0.9615 - val_loss: 1.0255 - val_accuracy: 0.8050
Epoch 43/100
1/16 [>.............................] - ETA: 0s - loss: 0.0565 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0580 - accuracy: 0.9677
11/16 [===================>..........] - ETA: 0s - loss: 0.0611 - accuracy: 0.9660
16/16 [==============================] - 0s 11ms/step - loss: 0.0620 - accuracy: 0.9644
16/16 [==============================] - 0s 21ms/step - loss: 0.0620 - accuracy: 0.9644 - val_loss: 1.0625 - val_accuracy: 0.8020
Epoch 44/100
1/16 [>.............................] - ETA: 0s - loss: 0.0465 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0522 - accuracy: 0.9717
11/16 [===================>..........] - ETA: 0s - loss: 0.0570 - accuracy: 0.9676
16/16 [==============================] - 0s 11ms/step - loss: 0.0635 - accuracy: 0.9613
16/16 [==============================] - 0s 21ms/step - loss: 0.0635 - accuracy: 0.9613 - val_loss: 1.0379 - val_accuracy: 0.8040
Epoch 45/100
1/16 [>.............................] - ETA: 0s - loss: 0.0539 - accuracy: 0.9700
6/16 [==========>...................] - ETA: 0s - loss: 0.0526 - accuracy: 0.9720
11/16 [===================>..........] - ETA: 0s - loss: 0.0559 - accuracy: 0.9669
15/16 [===========================>..] - ETA: 0s - loss: 0.0598 - accuracy: 0.9639
16/16 [==============================] - 0s 11ms/step - loss: 0.0619 - accuracy: 0.9622
16/16 [==============================] - 0s 21ms/step - loss: 0.0619 - accuracy: 0.9622 - val_loss: 1.0468 - val_accuracy: 0.8060
Epoch 46/100
1/16 [>.............................] - ETA: 0s - loss: 0.0462 - accuracy: 0.9820
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16/16 [==============================] - 0s 12ms/step - loss: 0.0612 - accuracy: 0.9623
16/16 [==============================] - 0s 22ms/step - loss: 0.0612 - accuracy: 0.9623 - val_loss: 1.0500 - val_accuracy: 0.8030
Epoch 47/100
1/16 [>.............................] - ETA: 0s - loss: 0.0573 - accuracy: 0.9720
5/16 [========>.....................] - ETA: 0s - loss: 0.0530 - accuracy: 0.9716
9/16 [===============>..............] - ETA: 0s - loss: 0.0523 - accuracy: 0.9702
14/16 [=========================>....] - ETA: 0s - loss: 0.0592 - accuracy: 0.9624
16/16 [==============================] - 0s 12ms/step - loss: 0.0606 - accuracy: 0.9607
16/16 [==============================] - 0s 21ms/step - loss: 0.0606 - accuracy: 0.9607 - val_loss: 1.0645 - val_accuracy: 0.8040
Epoch 48/100
1/16 [>.............................] - ETA: 0s - loss: 0.0627 - accuracy: 0.9620
5/16 [========>.....................] - ETA: 0s - loss: 0.0551 - accuracy: 0.9672
10/16 [=================>............] - ETA: 0s - loss: 0.0596 - accuracy: 0.9626
15/16 [===========================>..] - ETA: 0s - loss: 0.0611 - accuracy: 0.9605
16/16 [==============================] - 0s 12ms/step - loss: 0.0615 - accuracy: 0.9600
16/16 [==============================] - 0s 21ms/step - loss: 0.0615 - accuracy: 0.9600 - val_loss: 1.0518 - val_accuracy: 0.8030
Epoch 49/100
1/16 [>.............................] - ETA: 0s - loss: 0.0603 - accuracy: 0.9660
5/16 [========>.....................] - ETA: 0s - loss: 0.0524 - accuracy: 0.9704
9/16 [===============>..............] - ETA: 0s - loss: 0.0552 - accuracy: 0.9676
14/16 [=========================>....] - ETA: 0s - loss: 0.0583 - accuracy: 0.9641
16/16 [==============================] - 0s 12ms/step - loss: 0.0588 - accuracy: 0.9632
16/16 [==============================] - 0s 21ms/step - loss: 0.0588 - accuracy: 0.9632 - val_loss: 1.0584 - val_accuracy: 0.8070
Epoch 50/100
1/16 [>.............................] - ETA: 0s - loss: 0.0387 - accuracy: 0.9820
5/16 [========>.....................] - ETA: 0s - loss: 0.0556 - accuracy: 0.9672
9/16 [===============>..............] - ETA: 0s - loss: 0.0556 - accuracy: 0.9667
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16/16 [==============================] - 0s 13ms/step - loss: 0.0589 - accuracy: 0.9617
16/16 [==============================] - 0s 22ms/step - loss: 0.0589 - accuracy: 0.9617 - val_loss: 1.0630 - val_accuracy: 0.8040
Epoch 51/100
1/16 [>.............................] - ETA: 0s - loss: 0.0456 - accuracy: 0.9700
6/16 [==========>...................] - ETA: 0s - loss: 0.0557 - accuracy: 0.9660
11/16 [===================>..........] - ETA: 0s - loss: 0.0568 - accuracy: 0.9638
15/16 [===========================>..] - ETA: 0s - loss: 0.0578 - accuracy: 0.9616
16/16 [==============================] - 0s 12ms/step - loss: 0.0583 - accuracy: 0.9612
16/16 [==============================] - 0s 22ms/step - loss: 0.0583 - accuracy: 0.9612 - val_loss: 1.0722 - val_accuracy: 0.8070
Epoch 52/100
1/16 [>.............................] - ETA: 0s - loss: 0.0577 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0562 - accuracy: 0.9663
11/16 [===================>..........] - ETA: 0s - loss: 0.0587 - accuracy: 0.9631
16/16 [==============================] - 0s 11ms/step - loss: 0.0596 - accuracy: 0.9617
16/16 [==============================] - 0s 21ms/step - loss: 0.0596 - accuracy: 0.9617 - val_loss: 1.0670 - val_accuracy: 0.7990
Epoch 53/100
1/16 [>.............................] - ETA: 0s - loss: 0.0619 - accuracy: 0.9620
6/16 [==========>...................] - ETA: 0s - loss: 0.0534 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0549 - accuracy: 0.9656
15/16 [===========================>..] - ETA: 0s - loss: 0.0587 - accuracy: 0.9624
16/16 [==============================] - 0s 12ms/step - loss: 0.0589 - accuracy: 0.9619
16/16 [==============================] - 0s 21ms/step - loss: 0.0589 - accuracy: 0.9619 - val_loss: 1.0834 - val_accuracy: 0.8040
Epoch 54/100
1/16 [>.............................] - ETA: 0s - loss: 0.0407 - accuracy: 0.9820
5/16 [========>.....................] - ETA: 0s - loss: 0.0479 - accuracy: 0.9708
9/16 [===============>..............] - ETA: 0s - loss: 0.0521 - accuracy: 0.9682
14/16 [=========================>....] - ETA: 0s - loss: 0.0557 - accuracy: 0.9639
16/16 [==============================] - 0s 12ms/step - loss: 0.0587 - accuracy: 0.9610
16/16 [==============================] - 0s 21ms/step - loss: 0.0587 - accuracy: 0.9610 - val_loss: 1.0699 - val_accuracy: 0.8040
Epoch 55/100
1/16 [>.............................] - ETA: 0s - loss: 0.0505 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0500 - accuracy: 0.9663
11/16 [===================>..........] - ETA: 0s - loss: 0.0563 - accuracy: 0.9613
15/16 [===========================>..] - ETA: 0s - loss: 0.0583 - accuracy: 0.9592
16/16 [==============================] - 0s 12ms/step - loss: 0.0578 - accuracy: 0.9593
16/16 [==============================] - 0s 21ms/step - loss: 0.0578 - accuracy: 0.9593 - val_loss: 1.0943 - val_accuracy: 0.8010
Epoch 56/100
1/16 [>.............................] - ETA: 0s - loss: 0.0548 - accuracy: 0.9640
6/16 [==========>...................] - ETA: 0s - loss: 0.0523 - accuracy: 0.9707
10/16 [=================>............] - ETA: 0s - loss: 0.0558 - accuracy: 0.9648
15/16 [===========================>..] - ETA: 0s - loss: 0.0568 - accuracy: 0.9617
16/16 [==============================] - 0s 11ms/step - loss: 0.0574 - accuracy: 0.9614
16/16 [==============================] - 0s 21ms/step - loss: 0.0574 - accuracy: 0.9614 - val_loss: 1.0828 - val_accuracy: 0.8050
Epoch 57/100
1/16 [>.............................] - ETA: 0s - loss: 0.0437 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0516 - accuracy: 0.9663
10/16 [=================>............] - ETA: 0s - loss: 0.0526 - accuracy: 0.9664
15/16 [===========================>..] - ETA: 0s - loss: 0.0565 - accuracy: 0.9615
16/16 [==============================] - 0s 12ms/step - loss: 0.0572 - accuracy: 0.9607
16/16 [==============================] - 0s 21ms/step - loss: 0.0572 - accuracy: 0.9607 - val_loss: 1.0831 - val_accuracy: 0.8020
Epoch 58/100
1/16 [>.............................] - ETA: 0s - loss: 0.0517 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0526 - accuracy: 0.9713
10/16 [=================>............] - ETA: 0s - loss: 0.0522 - accuracy: 0.9688
15/16 [===========================>..] - ETA: 0s - loss: 0.0549 - accuracy: 0.9651
16/16 [==============================] - 0s 12ms/step - loss: 0.0568 - accuracy: 0.9632
16/16 [==============================] - 0s 21ms/step - loss: 0.0568 - accuracy: 0.9632 - val_loss: 1.0936 - val_accuracy: 0.8000
Epoch 59/100
1/16 [>.............................] - ETA: 0s - loss: 0.0327 - accuracy: 0.9820
6/16 [==========>...................] - ETA: 0s - loss: 0.0518 - accuracy: 0.9660
10/16 [=================>............] - ETA: 0s - loss: 0.0551 - accuracy: 0.9636
14/16 [=========================>....] - ETA: 0s - loss: 0.0559 - accuracy: 0.9620
16/16 [==============================] - 0s 12ms/step - loss: 0.0576 - accuracy: 0.9603
16/16 [==============================] - 0s 21ms/step - loss: 0.0576 - accuracy: 0.9603 - val_loss: 1.0929 - val_accuracy: 0.8040
Epoch 60/100
1/16 [>.............................] - ETA: 0s - loss: 0.0450 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0490 - accuracy: 0.9693
11/16 [===================>..........] - ETA: 0s - loss: 0.0547 - accuracy: 0.9653
15/16 [===========================>..] - ETA: 0s - loss: 0.0554 - accuracy: 0.9625
16/16 [==============================] - 0s 12ms/step - loss: 0.0575 - accuracy: 0.9608
16/16 [==============================] - 0s 21ms/step - loss: 0.0575 - accuracy: 0.9608 - val_loss: 1.0992 - val_accuracy: 0.8030
Epoch 61/100
1/16 [>.............................] - ETA: 0s - loss: 0.0607 - accuracy: 0.9560
5/16 [========>.....................] - ETA: 0s - loss: 0.0523 - accuracy: 0.9644
10/16 [=================>............] - ETA: 0s - loss: 0.0519 - accuracy: 0.9640
14/16 [=========================>....] - ETA: 0s - loss: 0.0554 - accuracy: 0.9609
16/16 [==============================] - 0s 12ms/step - loss: 0.0562 - accuracy: 0.9605
16/16 [==============================] - 0s 21ms/step - loss: 0.0562 - accuracy: 0.9605 - val_loss: 1.0959 - val_accuracy: 0.8030
Epoch 62/100
1/16 [>.............................] - ETA: 0s - loss: 0.0524 - accuracy: 0.9680
5/16 [========>.....................] - ETA: 0s - loss: 0.0472 - accuracy: 0.9692
9/16 [===============>..............] - ETA: 0s - loss: 0.0504 - accuracy: 0.9664
14/16 [=========================>....] - ETA: 0s - loss: 0.0549 - accuracy: 0.9614
16/16 [==============================] - 0s 12ms/step - loss: 0.0561 - accuracy: 0.9600
16/16 [==============================] - 0s 22ms/step - loss: 0.0561 - accuracy: 0.9600 - val_loss: 1.0982 - val_accuracy: 0.8040
Epoch 63/100
1/16 [>.............................] - ETA: 0s - loss: 0.0433 - accuracy: 0.9760
5/16 [========>.....................] - ETA: 0s - loss: 0.0429 - accuracy: 0.9724
9/16 [===============>..............] - ETA: 0s - loss: 0.0514 - accuracy: 0.9651
14/16 [=========================>....] - ETA: 0s - loss: 0.0539 - accuracy: 0.9614
16/16 [==============================] - 0s 12ms/step - loss: 0.0561 - accuracy: 0.9593
16/16 [==============================] - 0s 21ms/step - loss: 0.0561 - accuracy: 0.9593 - val_loss: 1.1052 - val_accuracy: 0.8030
Epoch 64/100
1/16 [>.............................] - ETA: 0s - loss: 0.0447 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0477 - accuracy: 0.9703
11/16 [===================>..........] - ETA: 0s - loss: 0.0512 - accuracy: 0.9655
16/16 [==============================] - 0s 11ms/step - loss: 0.0552 - accuracy: 0.9612
16/16 [==============================] - 0s 20ms/step - loss: 0.0552 - accuracy: 0.9612 - val_loss: 1.1035 - val_accuracy: 0.8030
Epoch 65/100
1/16 [>.............................] - ETA: 0s - loss: 0.0512 - accuracy: 0.9620
5/16 [========>.....................] - ETA: 0s - loss: 0.0515 - accuracy: 0.9680
9/16 [===============>..............] - ETA: 0s - loss: 0.0515 - accuracy: 0.9671
14/16 [=========================>....] - ETA: 0s - loss: 0.0545 - accuracy: 0.9617
16/16 [==============================] - 0s 12ms/step - loss: 0.0557 - accuracy: 0.9607
16/16 [==============================] - 0s 21ms/step - loss: 0.0557 - accuracy: 0.9607 - val_loss: 1.1193 - val_accuracy: 0.8040
Epoch 66/100
1/16 [>.............................] - ETA: 0s - loss: 0.0439 - accuracy: 0.9740
6/16 [==========>...................] - ETA: 0s - loss: 0.0533 - accuracy: 0.9673
11/16 [===================>..........] - ETA: 0s - loss: 0.0549 - accuracy: 0.9644
15/16 [===========================>..] - ETA: 0s - loss: 0.0551 - accuracy: 0.9629
16/16 [==============================] - 0s 12ms/step - loss: 0.0555 - accuracy: 0.9624
16/16 [==============================] - 0s 21ms/step - loss: 0.0555 - accuracy: 0.9624 - val_loss: 1.1120 - val_accuracy: 0.8010
Epoch 67/100
1/16 [>.............................] - ETA: 0s - loss: 0.0496 - accuracy: 0.9700
5/16 [========>.....................] - ETA: 0s - loss: 0.0459 - accuracy: 0.9720
9/16 [===============>..............] - ETA: 0s - loss: 0.0518 - accuracy: 0.9647
14/16 [=========================>....] - ETA: 0s - loss: 0.0549 - accuracy: 0.9617
16/16 [==============================] - 0s 12ms/step - loss: 0.0552 - accuracy: 0.9612
16/16 [==============================] - 0s 21ms/step - loss: 0.0552 - accuracy: 0.9612 - val_loss: 1.1202 - val_accuracy: 0.8050
Epoch 68/100
1/16 [>.............................] - ETA: 0s - loss: 0.0446 - accuracy: 0.9800
6/16 [==========>...................] - ETA: 0s - loss: 0.0478 - accuracy: 0.9710
11/16 [===================>..........] - ETA: 0s - loss: 0.0530 - accuracy: 0.9665
16/16 [==============================] - 0s 11ms/step - loss: 0.0556 - accuracy: 0.9629
16/16 [==============================] - 0s 21ms/step - loss: 0.0556 - accuracy: 0.9629 - val_loss: 1.1312 - val_accuracy: 0.8060
Epoch 69/100
1/16 [>.............................] - ETA: 0s - loss: 0.0314 - accuracy: 0.9820
6/16 [==========>...................] - ETA: 0s - loss: 0.0518 - accuracy: 0.9670
11/16 [===================>..........] - ETA: 0s - loss: 0.0522 - accuracy: 0.9655
15/16 [===========================>..] - ETA: 0s - loss: 0.0551 - accuracy: 0.9621
16/16 [==============================] - 0s 12ms/step - loss: 0.0548 - accuracy: 0.9622
16/16 [==============================] - 0s 21ms/step - loss: 0.0548 - accuracy: 0.9622 - val_loss: 1.1129 - val_accuracy: 0.7980
Epoch 70/100
1/16 [>.............................] - ETA: 0s - loss: 0.0374 - accuracy: 0.9780
6/16 [==========>...................] - ETA: 0s - loss: 0.0461 - accuracy: 0.9710
11/16 [===================>..........] - ETA: 0s - loss: 0.0492 - accuracy: 0.9669
16/16 [==============================] - 0s 11ms/step - loss: 0.0551 - accuracy: 0.9602
16/16 [==============================] - 0s 20ms/step - loss: 0.0551 - accuracy: 0.9602 - val_loss: 1.1379 - val_accuracy: 0.8040
Epoch 71/100
1/16 [>.............................] - ETA: 0s - loss: 0.0353 - accuracy: 0.9840
6/16 [==========>...................] - ETA: 0s - loss: 0.0497 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0515 - accuracy: 0.9636
16/16 [==============================] - 0s 11ms/step - loss: 0.0545 - accuracy: 0.9600
16/16 [==============================] - 0s 20ms/step - loss: 0.0545 - accuracy: 0.9600 - val_loss: 1.1269 - val_accuracy: 0.8010
Epoch 72/100
1/16 [>.............................] - ETA: 0s - loss: 0.0377 - accuracy: 0.9740
6/16 [==========>...................] - ETA: 0s - loss: 0.0482 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0501 - accuracy: 0.9669
16/16 [==============================] - 0s 11ms/step - loss: 0.0554 - accuracy: 0.9610
16/16 [==============================] - 0s 21ms/step - loss: 0.0554 - accuracy: 0.9610 - val_loss: 1.1285 - val_accuracy: 0.7990
Epoch 73/100
1/16 [>.............................] - ETA: 0s - loss: 0.0439 - accuracy: 0.9680
5/16 [========>.....................] - ETA: 0s - loss: 0.0532 - accuracy: 0.9672
10/16 [=================>............] - ETA: 0s - loss: 0.0544 - accuracy: 0.9638
15/16 [===========================>..] - ETA: 0s - loss: 0.0532 - accuracy: 0.9631
16/16 [==============================] - 0s 11ms/step - loss: 0.0544 - accuracy: 0.9618
16/16 [==============================] - 0s 21ms/step - loss: 0.0544 - accuracy: 0.9618 - val_loss: 1.1491 - val_accuracy: 0.8020
Epoch 74/100
1/16 [>.............................] - ETA: 0s - loss: 0.0464 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0492 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0523 - accuracy: 0.9653
16/16 [==============================] - 0s 11ms/step - loss: 0.0537 - accuracy: 0.9624
16/16 [==============================] - 0s 20ms/step - loss: 0.0537 - accuracy: 0.9624 - val_loss: 1.1395 - val_accuracy: 0.8020
Epoch 75/100
1/16 [>.............................] - ETA: 0s - loss: 0.0468 - accuracy: 0.9700
5/16 [========>.....................] - ETA: 0s - loss: 0.0476 - accuracy: 0.9708
10/16 [=================>............] - ETA: 0s - loss: 0.0506 - accuracy: 0.9658
15/16 [===========================>..] - ETA: 0s - loss: 0.0535 - accuracy: 0.9613
16/16 [==============================] - 0s 12ms/step - loss: 0.0542 - accuracy: 0.9607
16/16 [==============================] - 0s 21ms/step - loss: 0.0542 - accuracy: 0.9607 - val_loss: 1.1398 - val_accuracy: 0.8060
Epoch 76/100
1/16 [>.............................] - ETA: 0s - loss: 0.0408 - accuracy: 0.9780
6/16 [==========>...................] - ETA: 0s - loss: 0.0492 - accuracy: 0.9673
11/16 [===================>..........] - ETA: 0s - loss: 0.0524 - accuracy: 0.9645
15/16 [===========================>..] - ETA: 0s - loss: 0.0537 - accuracy: 0.9623
16/16 [==============================] - 0s 12ms/step - loss: 0.0546 - accuracy: 0.9612
16/16 [==============================] - 0s 21ms/step - loss: 0.0546 - accuracy: 0.9612 - val_loss: 1.1466 - val_accuracy: 0.8010
Epoch 77/100
1/16 [>.............................] - ETA: 0s - loss: 0.0533 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0553 - accuracy: 0.9643
11/16 [===================>..........] - ETA: 0s - loss: 0.0525 - accuracy: 0.9638
16/16 [==============================] - 0s 11ms/step - loss: 0.0542 - accuracy: 0.9609
16/16 [==============================] - 0s 20ms/step - loss: 0.0542 - accuracy: 0.9609 - val_loss: 1.1423 - val_accuracy: 0.8070
Epoch 78/100
1/16 [>.............................] - ETA: 0s - loss: 0.0551 - accuracy: 0.9620
6/16 [==========>...................] - ETA: 0s - loss: 0.0483 - accuracy: 0.9703
11/16 [===================>..........] - ETA: 0s - loss: 0.0505 - accuracy: 0.9660
16/16 [==============================] - 0s 11ms/step - loss: 0.0538 - accuracy: 0.9614
16/16 [==============================] - 0s 20ms/step - loss: 0.0538 - accuracy: 0.9614 - val_loss: 1.1447 - val_accuracy: 0.8010
Epoch 79/100
1/16 [>.............................] - ETA: 0s - loss: 0.0442 - accuracy: 0.9820
6/16 [==========>...................] - ETA: 0s - loss: 0.0479 - accuracy: 0.9687
11/16 [===================>..........] - ETA: 0s - loss: 0.0506 - accuracy: 0.9647
16/16 [==============================] - 0s 11ms/step - loss: 0.0531 - accuracy: 0.9610
16/16 [==============================] - 0s 21ms/step - loss: 0.0531 - accuracy: 0.9610 - val_loss: 1.1563 - val_accuracy: 0.8000
Epoch 80/100
1/16 [>.............................] - ETA: 0s - loss: 0.0486 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0473 - accuracy: 0.9680
11/16 [===================>..........] - ETA: 0s - loss: 0.0516 - accuracy: 0.9655
15/16 [===========================>..] - ETA: 0s - loss: 0.0543 - accuracy: 0.9619
16/16 [==============================] - 0s 12ms/step - loss: 0.0543 - accuracy: 0.9614
16/16 [==============================] - 0s 21ms/step - loss: 0.0543 - accuracy: 0.9614 - val_loss: 1.1695 - val_accuracy: 0.8040
Epoch 81/100
1/16 [>.............................] - ETA: 0s - loss: 0.0328 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0481 - accuracy: 0.9677
10/16 [=================>............] - ETA: 0s - loss: 0.0499 - accuracy: 0.9670
14/16 [=========================>....] - ETA: 0s - loss: 0.0536 - accuracy: 0.9639
16/16 [==============================] - 0s 12ms/step - loss: 0.0546 - accuracy: 0.9623
16/16 [==============================] - 0s 21ms/step - loss: 0.0546 - accuracy: 0.9623 - val_loss: 1.1445 - val_accuracy: 0.8030
Epoch 82/100
1/16 [>.............................] - ETA: 0s - loss: 0.0470 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0496 - accuracy: 0.9697
10/16 [=================>............] - ETA: 0s - loss: 0.0546 - accuracy: 0.9646
15/16 [===========================>..] - ETA: 0s - loss: 0.0522 - accuracy: 0.9643
16/16 [==============================] - 0s 12ms/step - loss: 0.0530 - accuracy: 0.9632
16/16 [==============================] - 0s 21ms/step - loss: 0.0530 - accuracy: 0.9632 - val_loss: 1.1556 - val_accuracy: 0.8010
Epoch 83/100
1/16 [>.............................] - ETA: 0s - loss: 0.0438 - accuracy: 0.9700
6/16 [==========>...................] - ETA: 0s - loss: 0.0478 - accuracy: 0.9673
11/16 [===================>..........] - ETA: 0s - loss: 0.0515 - accuracy: 0.9624
16/16 [==============================] - 0s 11ms/step - loss: 0.0533 - accuracy: 0.9600
16/16 [==============================] - 0s 21ms/step - loss: 0.0533 - accuracy: 0.9600 - val_loss: 1.1648 - val_accuracy: 0.8040
Epoch 84/100
1/16 [>.............................] - ETA: 0s - loss: 0.0566 - accuracy: 0.9580
6/16 [==========>...................] - ETA: 0s - loss: 0.0493 - accuracy: 0.9653
11/16 [===================>..........] - ETA: 0s - loss: 0.0514 - accuracy: 0.9635
16/16 [==============================] - 0s 12ms/step - loss: 0.0535 - accuracy: 0.9608
16/16 [==============================] - 0s 21ms/step - loss: 0.0535 - accuracy: 0.9608 - val_loss: 1.1580 - val_accuracy: 0.8010
Epoch 85/100
1/16 [>.............................] - ETA: 0s - loss: 0.0536 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0456 - accuracy: 0.9703
10/16 [=================>............] - ETA: 0s - loss: 0.0503 - accuracy: 0.9652
15/16 [===========================>..] - ETA: 0s - loss: 0.0533 - accuracy: 0.9609
16/16 [==============================] - 0s 11ms/step - loss: 0.0531 - accuracy: 0.9609
16/16 [==============================] - 0s 21ms/step - loss: 0.0531 - accuracy: 0.9609 - val_loss: 1.1722 - val_accuracy: 0.8010
Epoch 86/100
1/16 [>.............................] - ETA: 0s - loss: 0.0464 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0480 - accuracy: 0.9697
11/16 [===================>..........] - ETA: 0s - loss: 0.0506 - accuracy: 0.9665
16/16 [==============================] - 0s 11ms/step - loss: 0.0530 - accuracy: 0.9623
16/16 [==============================] - 0s 20ms/step - loss: 0.0530 - accuracy: 0.9623 - val_loss: 1.1614 - val_accuracy: 0.8020
Epoch 87/100
1/16 [>.............................] - ETA: 0s - loss: 0.0424 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0504 - accuracy: 0.9690
10/16 [=================>............] - ETA: 0s - loss: 0.0489 - accuracy: 0.9698
15/16 [===========================>..] - ETA: 0s - loss: 0.0517 - accuracy: 0.9651
16/16 [==============================] - 0s 12ms/step - loss: 0.0527 - accuracy: 0.9637
16/16 [==============================] - 0s 21ms/step - loss: 0.0527 - accuracy: 0.9637 - val_loss: 1.1711 - val_accuracy: 0.8070
Epoch 88/100
1/16 [>.............................] - ETA: 0s - loss: 0.0668 - accuracy: 0.9520
6/16 [==========>...................] - ETA: 0s - loss: 0.0533 - accuracy: 0.9660
11/16 [===================>..........] - ETA: 0s - loss: 0.0508 - accuracy: 0.9656
16/16 [==============================] - 0s 11ms/step - loss: 0.0526 - accuracy: 0.9618
16/16 [==============================] - 0s 20ms/step - loss: 0.0526 - accuracy: 0.9618 - val_loss: 1.1852 - val_accuracy: 0.8020
Epoch 89/100
1/16 [>.............................] - ETA: 0s - loss: 0.0325 - accuracy: 0.9800
5/16 [========>.....................] - ETA: 0s - loss: 0.0457 - accuracy: 0.9700
10/16 [=================>............] - ETA: 0s - loss: 0.0487 - accuracy: 0.9674
14/16 [=========================>....] - ETA: 0s - loss: 0.0508 - accuracy: 0.9634
16/16 [==============================] - 0s 12ms/step - loss: 0.0518 - accuracy: 0.9619
16/16 [==============================] - 0s 21ms/step - loss: 0.0518 - accuracy: 0.9619 - val_loss: 1.1678 - val_accuracy: 0.8010
Epoch 90/100
1/16 [>.............................] - ETA: 0s - loss: 0.0543 - accuracy: 0.9660
5/16 [========>.....................] - ETA: 0s - loss: 0.0519 - accuracy: 0.9704
9/16 [===============>..............] - ETA: 0s - loss: 0.0502 - accuracy: 0.9678
14/16 [=========================>....] - ETA: 0s - loss: 0.0520 - accuracy: 0.9644
16/16 [==============================] - 0s 12ms/step - loss: 0.0527 - accuracy: 0.9628
16/16 [==============================] - 0s 21ms/step - loss: 0.0527 - accuracy: 0.9628 - val_loss: 1.1752 - val_accuracy: 0.8010
Epoch 91/100
1/16 [>.............................] - ETA: 0s - loss: 0.0444 - accuracy: 0.9720
5/16 [========>.....................] - ETA: 0s - loss: 0.0407 - accuracy: 0.9760
10/16 [=================>............] - ETA: 0s - loss: 0.0483 - accuracy: 0.9682
15/16 [===========================>..] - ETA: 0s - loss: 0.0527 - accuracy: 0.9628
16/16 [==============================] - 0s 12ms/step - loss: 0.0521 - accuracy: 0.9629
16/16 [==============================] - 0s 21ms/step - loss: 0.0521 - accuracy: 0.9629 - val_loss: 1.1827 - val_accuracy: 0.8030
Epoch 92/100
1/16 [>.............................] - ETA: 0s - loss: 0.0494 - accuracy: 0.9660
5/16 [========>.....................] - ETA: 0s - loss: 0.0459 - accuracy: 0.9720
10/16 [=================>............] - ETA: 0s - loss: 0.0498 - accuracy: 0.9680
15/16 [===========================>..] - ETA: 0s - loss: 0.0507 - accuracy: 0.9647
16/16 [==============================] - 0s 12ms/step - loss: 0.0516 - accuracy: 0.9635
16/16 [==============================] - 0s 21ms/step - loss: 0.0516 - accuracy: 0.9635 - val_loss: 1.1781 - val_accuracy: 0.8010
Epoch 93/100
1/16 [>.............................] - ETA: 0s - loss: 0.0654 - accuracy: 0.9660
6/16 [==========>...................] - ETA: 0s - loss: 0.0483 - accuracy: 0.9707
11/16 [===================>..........] - ETA: 0s - loss: 0.0512 - accuracy: 0.9676
16/16 [==============================] - 0s 11ms/step - loss: 0.0521 - accuracy: 0.9642
16/16 [==============================] - 0s 20ms/step - loss: 0.0521 - accuracy: 0.9642 - val_loss: 1.1918 - val_accuracy: 0.8000
Epoch 94/100
1/16 [>.............................] - ETA: 0s - loss: 0.0422 - accuracy: 0.9760
6/16 [==========>...................] - ETA: 0s - loss: 0.0503 - accuracy: 0.9680
11/16 [===================>..........] - ETA: 0s - loss: 0.0487 - accuracy: 0.9682
15/16 [===========================>..] - ETA: 0s - loss: 0.0525 - accuracy: 0.9636
16/16 [==============================] - 0s 11ms/step - loss: 0.0519 - accuracy: 0.9639
16/16 [==============================] - 0s 20ms/step - loss: 0.0519 - accuracy: 0.9639 - val_loss: 1.1801 - val_accuracy: 0.8010
Epoch 95/100
1/16 [>.............................] - ETA: 0s - loss: 0.0423 - accuracy: 0.9740
6/16 [==========>...................] - ETA: 0s - loss: 0.0433 - accuracy: 0.9723
11/16 [===================>..........] - ETA: 0s - loss: 0.0491 - accuracy: 0.9645
15/16 [===========================>..] - ETA: 0s - loss: 0.0510 - accuracy: 0.9613
16/16 [==============================] - 0s 11ms/step - loss: 0.0523 - accuracy: 0.9599
16/16 [==============================] - 0s 21ms/step - loss: 0.0523 - accuracy: 0.9599 - val_loss: 1.1883 - val_accuracy: 0.8060
Epoch 96/100
1/16 [>.............................] - ETA: 0s - loss: 0.0495 - accuracy: 0.9720
6/16 [==========>...................] - ETA: 0s - loss: 0.0441 - accuracy: 0.9713
11/16 [===================>..........] - ETA: 0s - loss: 0.0480 - accuracy: 0.9673
15/16 [===========================>..] - ETA: 0s - loss: 0.0516 - accuracy: 0.9621
16/16 [==============================] - 0s 11ms/step - loss: 0.0514 - accuracy: 0.9617
16/16 [==============================] - 0s 21ms/step - loss: 0.0514 - accuracy: 0.9617 - val_loss: 1.1882 - val_accuracy: 0.8000
Epoch 97/100
1/16 [>.............................] - ETA: 0s - loss: 0.0373 - accuracy: 0.9820
5/16 [========>.....................] - ETA: 0s - loss: 0.0416 - accuracy: 0.9732
10/16 [=================>............] - ETA: 0s - loss: 0.0441 - accuracy: 0.9722
15/16 [===========================>..] - ETA: 0s - loss: 0.0506 - accuracy: 0.9637
16/16 [==============================] - 0s 12ms/step - loss: 0.0518 - accuracy: 0.9625
16/16 [==============================] - 0s 21ms/step - loss: 0.0518 - accuracy: 0.9625 - val_loss: 1.1936 - val_accuracy: 0.8000
Epoch 98/100
1/16 [>.............................] - ETA: 0s - loss: 0.0502 - accuracy: 0.9740
6/16 [==========>...................] - ETA: 0s - loss: 0.0489 - accuracy: 0.9713
10/16 [=================>............] - ETA: 0s - loss: 0.0482 - accuracy: 0.9694
14/16 [=========================>....] - ETA: 0s - loss: 0.0512 - accuracy: 0.9651
16/16 [==============================] - 0s 12ms/step - loss: 0.0522 - accuracy: 0.9633
16/16 [==============================] - 0s 21ms/step - loss: 0.0522 - accuracy: 0.9633 - val_loss: 1.1883 - val_accuracy: 0.7990
Epoch 99/100
1/16 [>.............................] - ETA: 0s - loss: 0.0470 - accuracy: 0.9680
6/16 [==========>...................] - ETA: 0s - loss: 0.0500 - accuracy: 0.9683
11/16 [===================>..........] - ETA: 0s - loss: 0.0508 - accuracy: 0.9655
16/16 [==============================] - 0s 11ms/step - loss: 0.0522 - accuracy: 0.9614
16/16 [==============================] - 0s 20ms/step - loss: 0.0522 - accuracy: 0.9614 - val_loss: 1.2060 - val_accuracy: 0.8030
Epoch 100/100
1/16 [>.............................] - ETA: 0s - loss: 0.0588 - accuracy: 0.9640
6/16 [==========>...................] - ETA: 0s - loss: 0.0491 - accuracy: 0.9667
11/16 [===================>..........] - ETA: 0s - loss: 0.0492 - accuracy: 0.9660
15/16 [===========================>..] - ETA: 0s - loss: 0.0512 - accuracy: 0.9632
16/16 [==============================] - 0s 11ms/step - loss: 0.0518 - accuracy: 0.9622
16/16 [==============================] - 0s 20ms/step - loss: 0.0518 - accuracy: 0.9622 - val_loss: 1.1903 - val_accuracy: 0.8020
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-15-38Z
Training run 2/8 (flags = list(128, 1e-04, 500, 30, "sigmoid"))
Using run directory runs/2020-11-02T21-16-15Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/30
1/16 [>.............................] - ETA: 0s - loss: 3.5618 - accuracy: 0.0080
4/16 [======>.......................] - ETA: 0s - loss: 3.5334 - accuracy: 0.0085
8/16 [==============>...............] - ETA: 0s - loss: 3.5042 - accuracy: 0.0093
11/16 [===================>..........] - ETA: 0s - loss: 3.4826 - accuracy: 0.0116
14/16 [=========================>....] - ETA: 0s - loss: 3.4625 - accuracy: 0.0126
16/16 [==============================] - 0s 16ms/step - loss: 3.4469 - accuracy: 0.0134
16/16 [==============================] - 1s 55ms/step - loss: 3.4469 - accuracy: 0.0134 - val_loss: 3.3071 - val_accuracy: 0.1430
Epoch 2/30
1/16 [>.............................] - ETA: 0s - loss: 3.3271 - accuracy: 0.1580
4/16 [======>.......................] - ETA: 0s - loss: 3.3053 - accuracy: 0.2980
7/16 [============>.................] - ETA: 0s - loss: 3.2831 - accuracy: 0.3263
10/16 [=================>............] - ETA: 0s - loss: 3.2677 - accuracy: 0.3332
14/16 [=========================>....] - ETA: 0s - loss: 3.2364 - accuracy: 0.3386
16/16 [==============================] - 0s 17ms/step - loss: 3.2267 - accuracy: 0.3388
16/16 [==============================] - 0s 27ms/step - loss: 3.2267 - accuracy: 0.3388 - val_loss: 3.0982 - val_accuracy: 0.3540
Epoch 3/30
1/16 [>.............................] - ETA: 0s - loss: 3.1040 - accuracy: 0.3600
4/16 [======>.......................] - ETA: 0s - loss: 3.1337 - accuracy: 0.3350
7/16 [============>.................] - ETA: 0s - loss: 3.1011 - accuracy: 0.3409
10/16 [=================>............] - ETA: 0s - loss: 3.0777 - accuracy: 0.3470
13/16 [=======================>......] - ETA: 0s - loss: 3.0507 - accuracy: 0.3506
16/16 [==============================] - 0s 18ms/step - loss: 3.0316 - accuracy: 0.3514
16/16 [==============================] - 0s 28ms/step - loss: 3.0316 - accuracy: 0.3514 - val_loss: 2.9178 - val_accuracy: 0.3540
Epoch 4/30
1/16 [>.............................] - ETA: 0s - loss: 2.9454 - accuracy: 0.3480
4/16 [======>.......................] - ETA: 0s - loss: 2.8988 - accuracy: 0.3575
7/16 [============>.................] - ETA: 0s - loss: 2.9026 - accuracy: 0.3526
10/16 [=================>............] - ETA: 0s - loss: 2.8871 - accuracy: 0.3522
13/16 [=======================>......] - ETA: 0s - loss: 2.8778 - accuracy: 0.3538
16/16 [==============================] - 0s 17ms/step - loss: 2.8681 - accuracy: 0.3514
16/16 [==============================] - 0s 27ms/step - loss: 2.8681 - accuracy: 0.3514 - val_loss: 2.7677 - val_accuracy: 0.3540
Epoch 5/30
1/16 [>.............................] - ETA: 0s - loss: 2.7789 - accuracy: 0.3560
4/16 [======>.......................] - ETA: 0s - loss: 2.7565 - accuracy: 0.3600
7/16 [============>.................] - ETA: 0s - loss: 2.7619 - accuracy: 0.3586
10/16 [=================>............] - ETA: 0s - loss: 2.7546 - accuracy: 0.3536
13/16 [=======================>......] - ETA: 0s - loss: 2.7486 - accuracy: 0.3497
16/16 [==============================] - 0s 17ms/step - loss: 2.7345 - accuracy: 0.3514
16/16 [==============================] - 0s 28ms/step - loss: 2.7345 - accuracy: 0.3514 - val_loss: 2.6503 - val_accuracy: 0.3540
Epoch 6/30
1/16 [>.............................] - ETA: 0s - loss: 2.6890 - accuracy: 0.3620
4/16 [======>.......................] - ETA: 0s - loss: 2.6856 - accuracy: 0.3420
7/16 [============>.................] - ETA: 0s - loss: 2.6627 - accuracy: 0.3426
10/16 [=================>............] - ETA: 0s - loss: 2.6470 - accuracy: 0.3472
13/16 [=======================>......] - ETA: 0s - loss: 2.6374 - accuracy: 0.3489
16/16 [==============================] - 0s 18ms/step - loss: 2.6318 - accuracy: 0.3514
16/16 [==============================] - 0s 29ms/step - loss: 2.6318 - accuracy: 0.3514 - val_loss: 2.5608 - val_accuracy: 0.3540
Epoch 7/30
1/16 [>.............................] - ETA: 0s - loss: 2.5829 - accuracy: 0.3500
4/16 [======>.......................] - ETA: 0s - loss: 2.5790 - accuracy: 0.3485
7/16 [============>.................] - ETA: 0s - loss: 2.5755 - accuracy: 0.3497
10/16 [=================>............] - ETA: 0s - loss: 2.5590 - accuracy: 0.3544
13/16 [=======================>......] - ETA: 0s - loss: 2.5586 - accuracy: 0.3500
16/16 [==============================] - 0s 18ms/step - loss: 2.5548 - accuracy: 0.3514
16/16 [==============================] - 0s 29ms/step - loss: 2.5548 - accuracy: 0.3514 - val_loss: 2.4949 - val_accuracy: 0.3540
Epoch 8/30
1/16 [>.............................] - ETA: 0s - loss: 2.5396 - accuracy: 0.3400
4/16 [======>.......................] - ETA: 0s - loss: 2.5166 - accuracy: 0.3500
7/16 [============>.................] - ETA: 0s - loss: 2.5125 - accuracy: 0.3549
10/16 [=================>............] - ETA: 0s - loss: 2.4932 - accuracy: 0.3576
13/16 [=======================>......] - ETA: 0s - loss: 2.5085 - accuracy: 0.3526
16/16 [==============================] - 0s 20ms/step - loss: 2.4983 - accuracy: 0.3514
16/16 [==============================] - 0s 31ms/step - loss: 2.4983 - accuracy: 0.3514 - val_loss: 2.4480 - val_accuracy: 0.3540
Epoch 9/30
1/16 [>.............................] - ETA: 0s - loss: 2.4515 - accuracy: 0.3340
4/16 [======>.......................] - ETA: 0s - loss: 2.4549 - accuracy: 0.3585
7/16 [============>.................] - ETA: 0s - loss: 2.4467 - accuracy: 0.3589
10/16 [=================>............] - ETA: 0s - loss: 2.4423 - accuracy: 0.3542
13/16 [=======================>......] - ETA: 0s - loss: 2.4505 - accuracy: 0.3523
16/16 [==============================] - 0s 20ms/step - loss: 2.4583 - accuracy: 0.3514
16/16 [==============================] - 0s 31ms/step - loss: 2.4583 - accuracy: 0.3514 - val_loss: 2.4139 - val_accuracy: 0.3540
Epoch 10/30
1/16 [>.............................] - ETA: 0s - loss: 2.4356 - accuracy: 0.3820
4/16 [======>.......................] - ETA: 0s - loss: 2.4378 - accuracy: 0.3580
7/16 [============>.................] - ETA: 0s - loss: 2.4450 - accuracy: 0.3506
9/16 [===============>..............] - ETA: 0s - loss: 2.4415 - accuracy: 0.3491
11/16 [===================>..........] - ETA: 0s - loss: 2.4389 - accuracy: 0.3476
13/16 [=======================>......] - ETA: 0s - loss: 2.4342 - accuracy: 0.3517
16/16 [==============================] - 0s 23ms/step - loss: 2.4282 - accuracy: 0.3514
16/16 [==============================] - 1s 33ms/step - loss: 2.4282 - accuracy: 0.3514 - val_loss: 2.3893 - val_accuracy: 0.3540
Epoch 11/30
1/16 [>.............................] - ETA: 0s - loss: 2.3818 - accuracy: 0.3640
4/16 [======>.......................] - ETA: 0s - loss: 2.4054 - accuracy: 0.3560
7/16 [============>.................] - ETA: 0s - loss: 2.3998 - accuracy: 0.3586
10/16 [=================>............] - ETA: 0s - loss: 2.3874 - accuracy: 0.3602
13/16 [=======================>......] - ETA: 0s - loss: 2.3981 - accuracy: 0.3538
16/16 [==============================] - 0s 22ms/step - loss: 2.4057 - accuracy: 0.3514
16/16 [==============================] - 1s 34ms/step - loss: 2.4057 - accuracy: 0.3514 - val_loss: 2.3698 - val_accuracy: 0.3540
Epoch 12/30
1/16 [>.............................] - ETA: 0s - loss: 2.3355 - accuracy: 0.3660
3/16 [====>.........................] - ETA: 0s - loss: 2.3749 - accuracy: 0.3640
5/16 [========>.....................] - ETA: 0s - loss: 2.3830 - accuracy: 0.3600
7/16 [============>.................] - ETA: 0s - loss: 2.3773 - accuracy: 0.3606
10/16 [=================>............] - ETA: 0s - loss: 2.3852 - accuracy: 0.3574
13/16 [=======================>......] - ETA: 0s - loss: 2.3973 - accuracy: 0.3506
16/16 [==============================] - 0s 23ms/step - loss: 2.3869 - accuracy: 0.3514
16/16 [==============================] - 1s 36ms/step - loss: 2.3869 - accuracy: 0.3514 - val_loss: 2.3531 - val_accuracy: 0.3540
Epoch 13/30
1/16 [>.............................] - ETA: 0s - loss: 2.4193 - accuracy: 0.3340
3/16 [====>.........................] - ETA: 0s - loss: 2.3816 - accuracy: 0.3460
5/16 [========>.....................] - ETA: 0s - loss: 2.3845 - accuracy: 0.3396
7/16 [============>.................] - ETA: 0s - loss: 2.3794 - accuracy: 0.3443
9/16 [===============>..............] - ETA: 0s - loss: 2.3763 - accuracy: 0.3469
11/16 [===================>..........] - ETA: 0s - loss: 2.3668 - accuracy: 0.3522
13/16 [=======================>......] - ETA: 0s - loss: 2.3779 - accuracy: 0.3503
15/16 [===========================>..] - ETA: 0s - loss: 2.3743 - accuracy: 0.3507
16/16 [==============================] - 0s 26ms/step - loss: 2.3705 - accuracy: 0.3514
16/16 [==============================] - 1s 38ms/step - loss: 2.3705 - accuracy: 0.3514 - val_loss: 2.3384 - val_accuracy: 0.3540
Epoch 14/30
1/16 [>.............................] - ETA: 0s - loss: 2.2966 - accuracy: 0.3600
3/16 [====>.........................] - ETA: 0s - loss: 2.3570 - accuracy: 0.3553
5/16 [========>.....................] - ETA: 0s - loss: 2.3349 - accuracy: 0.3672
7/16 [============>.................] - ETA: 0s - loss: 2.3434 - accuracy: 0.3631
9/16 [===============>..............] - ETA: 0s - loss: 2.3360 - accuracy: 0.3596
11/16 [===================>..........] - ETA: 0s - loss: 2.3418 - accuracy: 0.3587
13/16 [=======================>......] - ETA: 0s - loss: 2.3535 - accuracy: 0.3551
15/16 [===========================>..] - ETA: 0s - loss: 2.3528 - accuracy: 0.3552
16/16 [==============================] - 0s 27ms/step - loss: 2.3551 - accuracy: 0.3514
16/16 [==============================] - 1s 39ms/step - loss: 2.3551 - accuracy: 0.3514 - val_loss: 2.3240 - val_accuracy: 0.3540
Epoch 15/30
1/16 [>.............................] - ETA: 0s - loss: 2.3507 - accuracy: 0.3260
3/16 [====>.........................] - ETA: 0s - loss: 2.3150 - accuracy: 0.3400
5/16 [========>.....................] - ETA: 0s - loss: 2.3392 - accuracy: 0.3464
7/16 [============>.................] - ETA: 0s - loss: 2.3631 - accuracy: 0.3371
9/16 [===============>..............] - ETA: 0s - loss: 2.3505 - accuracy: 0.3467
11/16 [===================>..........] - ETA: 0s - loss: 2.3407 - accuracy: 0.3498
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16/16 [==============================] - 0s 29ms/step - loss: 2.3398 - accuracy: 0.3518
16/16 [==============================] - 1s 42ms/step - loss: 2.3398 - accuracy: 0.3518 - val_loss: 2.3092 - val_accuracy: 0.3560
Epoch 16/30
1/16 [>.............................] - ETA: 0s - loss: 2.3263 - accuracy: 0.3860
3/16 [====>.........................] - ETA: 0s - loss: 2.2673 - accuracy: 0.3733
5/16 [========>.....................] - ETA: 0s - loss: 2.3209 - accuracy: 0.3644
7/16 [============>.................] - ETA: 0s - loss: 2.3191 - accuracy: 0.3671
9/16 [===============>..............] - ETA: 0s - loss: 2.3185 - accuracy: 0.3624
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13/16 [=======================>......] - ETA: 0s - loss: 2.3236 - accuracy: 0.3557
15/16 [===========================>..] - ETA: 0s - loss: 2.3192 - accuracy: 0.3539
16/16 [==============================] - 0s 30ms/step - loss: 2.3242 - accuracy: 0.3534
16/16 [==============================] - 1s 44ms/step - loss: 2.3242 - accuracy: 0.3534 - val_loss: 2.2938 - val_accuracy: 0.3620
Epoch 17/30
1/16 [>.............................] - ETA: 0s - loss: 2.2305 - accuracy: 0.3780
3/16 [====>.........................] - ETA: 0s - loss: 2.2704 - accuracy: 0.3747
5/16 [========>.....................] - ETA: 0s - loss: 2.2867 - accuracy: 0.3672
7/16 [============>.................] - ETA: 0s - loss: 2.3047 - accuracy: 0.3611
9/16 [===============>..............] - ETA: 0s - loss: 2.3125 - accuracy: 0.3573
11/16 [===================>..........] - ETA: 0s - loss: 2.3144 - accuracy: 0.3584
13/16 [=======================>......] - ETA: 0s - loss: 2.3108 - accuracy: 0.3597
15/16 [===========================>..] - ETA: 0s - loss: 2.3123 - accuracy: 0.3615
16/16 [==============================] - 1s 33ms/step - loss: 2.3074 - accuracy: 0.3611
16/16 [==============================] - 1s 47ms/step - loss: 2.3074 - accuracy: 0.3611 - val_loss: 2.2771 - val_accuracy: 0.3670
Epoch 18/30
1/16 [>.............................] - ETA: 0s - loss: 2.2832 - accuracy: 0.3480
3/16 [====>.........................] - ETA: 0s - loss: 2.2923 - accuracy: 0.3620
5/16 [========>.....................] - ETA: 0s - loss: 2.2518 - accuracy: 0.3708
7/16 [============>.................] - ETA: 0s - loss: 2.2660 - accuracy: 0.3697
9/16 [===============>..............] - ETA: 0s - loss: 2.2751 - accuracy: 0.3713
11/16 [===================>..........] - ETA: 0s - loss: 2.2876 - accuracy: 0.3695
13/16 [=======================>......] - ETA: 0s - loss: 2.2907 - accuracy: 0.3683
15/16 [===========================>..] - ETA: 0s - loss: 2.2979 - accuracy: 0.3679
16/16 [==============================] - 1s 34ms/step - loss: 2.2897 - accuracy: 0.3700
16/16 [==============================] - 1s 50ms/step - loss: 2.2897 - accuracy: 0.3700 - val_loss: 2.2594 - val_accuracy: 0.3780
Epoch 19/30
1/16 [>.............................] - ETA: 0s - loss: 2.4032 - accuracy: 0.3480
3/16 [====>.........................] - ETA: 0s - loss: 2.3182 - accuracy: 0.3627
5/16 [========>.....................] - ETA: 0s - loss: 2.2668 - accuracy: 0.3848
7/16 [============>.................] - ETA: 0s - loss: 2.2662 - accuracy: 0.3797
9/16 [===============>..............] - ETA: 0s - loss: 2.2730 - accuracy: 0.3793
11/16 [===================>..........] - ETA: 0s - loss: 2.2707 - accuracy: 0.3785
13/16 [=======================>......] - ETA: 0s - loss: 2.2691 - accuracy: 0.3772
15/16 [===========================>..] - ETA: 0s - loss: 2.2689 - accuracy: 0.3784
16/16 [==============================] - 1s 37ms/step - loss: 2.2706 - accuracy: 0.3789
16/16 [==============================] - 1s 52ms/step - loss: 2.2706 - accuracy: 0.3789 - val_loss: 2.2404 - val_accuracy: 0.3880
Epoch 20/30
1/16 [>.............................] - ETA: 0s - loss: 2.2348 - accuracy: 0.4020
3/16 [====>.........................] - ETA: 0s - loss: 2.2129 - accuracy: 0.3893
5/16 [========>.....................] - ETA: 0s - loss: 2.2209 - accuracy: 0.3832
7/16 [============>.................] - ETA: 0s - loss: 2.2614 - accuracy: 0.3803
9/16 [===============>..............] - ETA: 0s - loss: 2.2570 - accuracy: 0.3842
11/16 [===================>..........] - ETA: 0s - loss: 2.2462 - accuracy: 0.3858
13/16 [=======================>......] - ETA: 0s - loss: 2.2503 - accuracy: 0.3857
15/16 [===========================>..] - ETA: 0s - loss: 2.2522 - accuracy: 0.3880
16/16 [==============================] - 1s 40ms/step - loss: 2.2502 - accuracy: 0.3896
16/16 [==============================] - 1s 55ms/step - loss: 2.2502 - accuracy: 0.3896 - val_loss: 2.2196 - val_accuracy: 0.3980
Epoch 21/30
1/16 [>.............................] - ETA: 0s - loss: 2.2712 - accuracy: 0.4080
3/16 [====>.........................] - ETA: 0s - loss: 2.2551 - accuracy: 0.3913
5/16 [========>.....................] - ETA: 0s - loss: 2.1847 - accuracy: 0.4016
7/16 [============>.................] - ETA: 0s - loss: 2.2281 - accuracy: 0.3960
9/16 [===============>..............] - ETA: 0s - loss: 2.2177 - accuracy: 0.3969
11/16 [===================>..........] - ETA: 0s - loss: 2.2146 - accuracy: 0.4013
13/16 [=======================>......] - ETA: 0s - loss: 2.2154 - accuracy: 0.4008
15/16 [===========================>..] - ETA: 0s - loss: 2.2297 - accuracy: 0.3989
16/16 [==============================] - 1s 42ms/step - loss: 2.2285 - accuracy: 0.4009
16/16 [==============================] - 1s 59ms/step - loss: 2.2285 - accuracy: 0.4009 - val_loss: 2.1981 - val_accuracy: 0.4110
Epoch 22/30
1/16 [>.............................] - ETA: 0s - loss: 2.2576 - accuracy: 0.4080
2/16 [==>...........................] - ETA: 0s - loss: 2.2739 - accuracy: 0.4010
4/16 [======>.......................] - ETA: 0s - loss: 2.1970 - accuracy: 0.4275
6/16 [==========>...................] - ETA: 0s - loss: 2.1853 - accuracy: 0.4217
8/16 [==============>...............] - ETA: 0s - loss: 2.1848 - accuracy: 0.4215
10/16 [=================>............] - ETA: 0s - loss: 2.1982 - accuracy: 0.4130
12/16 [=====================>........] - ETA: 0s - loss: 2.2161 - accuracy: 0.4083
14/16 [=========================>....] - ETA: 0s - loss: 2.2051 - accuracy: 0.4116
16/16 [==============================] - 1s 43ms/step - loss: 2.2056 - accuracy: 0.4126
16/16 [==============================] - 1s 60ms/step - loss: 2.2056 - accuracy: 0.4126 - val_loss: 2.1756 - val_accuracy: 0.4260
Epoch 23/30
1/16 [>.............................] - ETA: 0s - loss: 2.2676 - accuracy: 0.3980
2/16 [==>...........................] - ETA: 0s - loss: 2.2206 - accuracy: 0.4160
3/16 [====>.........................] - ETA: 0s - loss: 2.1711 - accuracy: 0.4313
5/16 [========>.....................] - ETA: 0s - loss: 2.1808 - accuracy: 0.4296
7/16 [============>.................] - ETA: 0s - loss: 2.2142 - accuracy: 0.4217
9/16 [===============>..............] - ETA: 0s - loss: 2.2087 - accuracy: 0.4256
11/16 [===================>..........] - ETA: 0s - loss: 2.1943 - accuracy: 0.4278
13/16 [=======================>......] - ETA: 0s - loss: 2.1918 - accuracy: 0.4298
15/16 [===========================>..] - ETA: 0s - loss: 2.1873 - accuracy: 0.4336
16/16 [==============================] - 1s 43ms/step - loss: 2.1819 - accuracy: 0.4352
16/16 [==============================] - 1s 59ms/step - loss: 2.1819 - accuracy: 0.4352 - val_loss: 2.1525 - val_accuracy: 0.4580
Epoch 24/30
1/16 [>.............................] - ETA: 0s - loss: 2.1815 - accuracy: 0.4540
3/16 [====>.........................] - ETA: 0s - loss: 2.1880 - accuracy: 0.4407
5/16 [========>.....................] - ETA: 0s - loss: 2.1647 - accuracy: 0.4548
7/16 [============>.................] - ETA: 0s - loss: 2.1649 - accuracy: 0.4589
9/16 [===============>..............] - ETA: 0s - loss: 2.1792 - accuracy: 0.4522
11/16 [===================>..........] - ETA: 0s - loss: 2.1773 - accuracy: 0.4540
13/16 [=======================>......] - ETA: 0s - loss: 2.1727 - accuracy: 0.4558
15/16 [===========================>..] - ETA: 0s - loss: 2.1644 - accuracy: 0.4592
16/16 [==============================] - 1s 43ms/step - loss: 2.1580 - accuracy: 0.4617
16/16 [==============================] - 1s 60ms/step - loss: 2.1580 - accuracy: 0.4617 - val_loss: 2.1290 - val_accuracy: 0.4740
Epoch 25/30
1/16 [>.............................] - ETA: 0s - loss: 2.1997 - accuracy: 0.4900
3/16 [====>.........................] - ETA: 0s - loss: 2.2204 - accuracy: 0.4680
5/16 [========>.....................] - ETA: 0s - loss: 2.1851 - accuracy: 0.4748
7/16 [============>.................] - ETA: 0s - loss: 2.1617 - accuracy: 0.4714
9/16 [===============>..............] - ETA: 0s - loss: 2.1387 - accuracy: 0.4760
11/16 [===================>..........] - ETA: 0s - loss: 2.1417 - accuracy: 0.4749
13/16 [=======================>......] - ETA: 0s - loss: 2.1399 - accuracy: 0.4757
15/16 [===========================>..] - ETA: 0s - loss: 2.1327 - accuracy: 0.4787
16/16 [==============================] - 1s 41ms/step - loss: 2.1336 - accuracy: 0.4783
16/16 [==============================] - 1s 56ms/step - loss: 2.1336 - accuracy: 0.4783 - val_loss: 2.1058 - val_accuracy: 0.4820
Epoch 26/30
1/16 [>.............................] - ETA: 0s - loss: 2.1161 - accuracy: 0.5240
3/16 [====>.........................] - ETA: 0s - loss: 2.1266 - accuracy: 0.4933
5/16 [========>.....................] - ETA: 0s - loss: 2.1506 - accuracy: 0.4888
7/16 [============>.................] - ETA: 0s - loss: 2.1437 - accuracy: 0.4863
9/16 [===============>..............] - ETA: 0s - loss: 2.1326 - accuracy: 0.4871
11/16 [===================>..........] - ETA: 0s - loss: 2.1256 - accuracy: 0.4885
13/16 [=======================>......] - ETA: 0s - loss: 2.1241 - accuracy: 0.4908
15/16 [===========================>..] - ETA: 0s - loss: 2.1128 - accuracy: 0.4939
16/16 [==============================] - 1s 37ms/step - loss: 2.1096 - accuracy: 0.4940
16/16 [==============================] - 1s 51ms/step - loss: 2.1096 - accuracy: 0.4940 - val_loss: 2.0829 - val_accuracy: 0.4960
Epoch 27/30
1/16 [>.............................] - ETA: 0s - loss: 2.1183 - accuracy: 0.4880
3/16 [====>.........................] - ETA: 0s - loss: 2.0858 - accuracy: 0.4933
5/16 [========>.....................] - ETA: 0s - loss: 2.0804 - accuracy: 0.5004
7/16 [============>.................] - ETA: 0s - loss: 2.1123 - accuracy: 0.4974
9/16 [===============>..............] - ETA: 0s - loss: 2.1055 - accuracy: 0.4973
11/16 [===================>..........] - ETA: 0s - loss: 2.0813 - accuracy: 0.5022
13/16 [=======================>......] - ETA: 0s - loss: 2.1008 - accuracy: 0.5002
15/16 [===========================>..] - ETA: 0s - loss: 2.0940 - accuracy: 0.5017
16/16 [==============================] - 1s 35ms/step - loss: 2.0857 - accuracy: 0.5050
16/16 [==============================] - 1s 49ms/step - loss: 2.0857 - accuracy: 0.5050 - val_loss: 2.0607 - val_accuracy: 0.5050
Epoch 28/30
1/16 [>.............................] - ETA: 0s - loss: 2.0244 - accuracy: 0.5300
3/16 [====>.........................] - ETA: 0s - loss: 2.0102 - accuracy: 0.5327
5/16 [========>.....................] - ETA: 0s - loss: 2.0620 - accuracy: 0.5192
7/16 [============>.................] - ETA: 0s - loss: 2.0682 - accuracy: 0.5143
9/16 [===============>..............] - ETA: 0s - loss: 2.0704 - accuracy: 0.5151
11/16 [===================>..........] - ETA: 0s - loss: 2.0672 - accuracy: 0.5158
13/16 [=======================>......] - ETA: 0s - loss: 2.0815 - accuracy: 0.5118
15/16 [===========================>..] - ETA: 0s - loss: 2.0647 - accuracy: 0.5144
16/16 [==============================] - 0s 30ms/step - loss: 2.0623 - accuracy: 0.5148
16/16 [==============================] - 1s 43ms/step - loss: 2.0623 - accuracy: 0.5148 - val_loss: 2.0389 - val_accuracy: 0.5150
Epoch 29/30
1/16 [>.............................] - ETA: 0s - loss: 2.1386 - accuracy: 0.5060
3/16 [====>.........................] - ETA: 0s - loss: 2.0271 - accuracy: 0.5233
5/16 [========>.....................] - ETA: 0s - loss: 2.0473 - accuracy: 0.5184
7/16 [============>.................] - ETA: 0s - loss: 2.0465 - accuracy: 0.5189
9/16 [===============>..............] - ETA: 0s - loss: 2.0515 - accuracy: 0.5202
11/16 [===================>..........] - ETA: 0s - loss: 2.0640 - accuracy: 0.5182
13/16 [=======================>......] - ETA: 0s - loss: 2.0518 - accuracy: 0.5206
15/16 [===========================>..] - ETA: 0s - loss: 2.0393 - accuracy: 0.5237
16/16 [==============================] - 0s 29ms/step - loss: 2.0393 - accuracy: 0.5226
16/16 [==============================] - 1s 42ms/step - loss: 2.0393 - accuracy: 0.5226 - val_loss: 2.0177 - val_accuracy: 0.5230
Epoch 30/30
1/16 [>.............................] - ETA: 0s - loss: 2.0781 - accuracy: 0.5160
3/16 [====>.........................] - ETA: 0s - loss: 2.0347 - accuracy: 0.5173
5/16 [========>.....................] - ETA: 0s - loss: 2.0325 - accuracy: 0.5216
7/16 [============>.................] - ETA: 0s - loss: 2.0474 - accuracy: 0.5166
9/16 [===============>..............] - ETA: 0s - loss: 2.0427 - accuracy: 0.5158
11/16 [===================>..........] - ETA: 0s - loss: 2.0333 - accuracy: 0.5189
13/16 [=======================>......] - ETA: 0s - loss: 2.0337 - accuracy: 0.5212
15/16 [===========================>..] - ETA: 0s - loss: 2.0245 - accuracy: 0.5249
16/16 [==============================] - 0s 27ms/step - loss: 2.0166 - accuracy: 0.5268
16/16 [==============================] - 1s 40ms/step - loss: 2.0166 - accuracy: 0.5268 - val_loss: 1.9971 - val_accuracy: 0.5260
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-16-15Z
Training run 3/8 (flags = list(128, 0.01, 200, 30, "relu"))
Using run directory runs/2020-11-02T21-16-38Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/30
1/40 [..............................] - ETA: 0s - loss: 3.8409 - accuracy: 0.0050
6/40 [===>..........................] - ETA: 0s - loss: 2.8484 - accuracy: 0.3683
11/40 [=======>......................] - ETA: 0s - loss: 2.4133 - accuracy: 0.4577
17/40 [===========>..................] - ETA: 0s - loss: 2.1102 - accuracy: 0.5306
22/40 [===============>..............] - ETA: 0s - loss: 1.9450 - accuracy: 0.5657
27/40 [===================>..........] - ETA: 0s - loss: 1.8244 - accuracy: 0.5935
32/40 [=======================>......] - ETA: 0s - loss: 1.7491 - accuracy: 0.6083
37/40 [==========================>...] - ETA: 0s - loss: 1.6784 - accuracy: 0.6218
40/40 [==============================] - 0s 10ms/step - loss: 1.6366 - accuracy: 0.6300
40/40 [==============================] - 1s 27ms/step - loss: 1.6366 - accuracy: 0.6300 - val_loss: 1.1564 - val_accuracy: 0.7390
Epoch 2/30
1/40 [..............................] - ETA: 0s - loss: 1.0083 - accuracy: 0.7600
7/40 [====>.........................] - ETA: 0s - loss: 0.8376 - accuracy: 0.7979
13/40 [========>.....................] - ETA: 0s - loss: 0.8306 - accuracy: 0.7992
19/40 [=============>................] - ETA: 0s - loss: 0.7919 - accuracy: 0.8024
24/40 [=================>............] - ETA: 0s - loss: 0.7778 - accuracy: 0.8050
29/40 [====================>.........] - ETA: 0s - loss: 0.7836 - accuracy: 0.8048
34/40 [========================>.....] - ETA: 0s - loss: 0.7865 - accuracy: 0.8038
39/40 [============================>.] - ETA: 0s - loss: 0.7841 - accuracy: 0.8049
40/40 [==============================] - 0s 10ms/step - loss: 0.7838 - accuracy: 0.8049
40/40 [==============================] - 1s 14ms/step - loss: 0.7838 - accuracy: 0.8049 - val_loss: 1.0223 - val_accuracy: 0.7690
Epoch 3/30
1/40 [..............................] - ETA: 0s - loss: 0.5870 - accuracy: 0.8350
6/40 [===>..........................] - ETA: 0s - loss: 0.5336 - accuracy: 0.8675
11/40 [=======>......................] - ETA: 0s - loss: 0.5043 - accuracy: 0.8705
17/40 [===========>..................] - ETA: 0s - loss: 0.4918 - accuracy: 0.8697
23/40 [================>.............] - ETA: 0s - loss: 0.4935 - accuracy: 0.8704
28/40 [====================>.........] - ETA: 0s - loss: 0.4959 - accuracy: 0.8707
33/40 [=======================>......] - ETA: 0s - loss: 0.4814 - accuracy: 0.8732
39/40 [============================>.] - ETA: 0s - loss: 0.4790 - accuracy: 0.8749
40/40 [==============================] - 0s 10ms/step - loss: 0.4791 - accuracy: 0.8748
40/40 [==============================] - 1s 14ms/step - loss: 0.4791 - accuracy: 0.8748 - val_loss: 0.9829 - val_accuracy: 0.7770
Epoch 4/30
1/40 [..............................] - ETA: 0s - loss: 0.3231 - accuracy: 0.9250
7/40 [====>.........................] - ETA: 0s - loss: 0.2839 - accuracy: 0.9200
13/40 [========>.....................] - ETA: 0s - loss: 0.2838 - accuracy: 0.9188
19/40 [=============>................] - ETA: 0s - loss: 0.2874 - accuracy: 0.9187
24/40 [=================>............] - ETA: 0s - loss: 0.2950 - accuracy: 0.9187
29/40 [====================>.........] - ETA: 0s - loss: 0.2984 - accuracy: 0.9191
34/40 [========================>.....] - ETA: 0s - loss: 0.3150 - accuracy: 0.9160
40/40 [==============================] - 0s 10ms/step - loss: 0.3193 - accuracy: 0.9142
40/40 [==============================] - 1s 14ms/step - loss: 0.3193 - accuracy: 0.9142 - val_loss: 1.0202 - val_accuracy: 0.7890
Epoch 5/30
1/40 [..............................] - ETA: 0s - loss: 0.2234 - accuracy: 0.9450
7/40 [====>.........................] - ETA: 0s - loss: 0.1922 - accuracy: 0.9521
13/40 [========>.....................] - ETA: 0s - loss: 0.2113 - accuracy: 0.9465
18/40 [============>.................] - ETA: 0s - loss: 0.2140 - accuracy: 0.9450
23/40 [================>.............] - ETA: 0s - loss: 0.2182 - accuracy: 0.9433
28/40 [====================>.........] - ETA: 0s - loss: 0.2183 - accuracy: 0.9438
33/40 [=======================>......] - ETA: 0s - loss: 0.2321 - accuracy: 0.9386
38/40 [===========================>..] - ETA: 0s - loss: 0.2420 - accuracy: 0.9374
40/40 [==============================] - 0s 10ms/step - loss: 0.2407 - accuracy: 0.9371
40/40 [==============================] - 1s 14ms/step - loss: 0.2407 - accuracy: 0.9371 - val_loss: 1.0516 - val_accuracy: 0.7840
Epoch 6/30
1/40 [..............................] - ETA: 0s - loss: 0.1945 - accuracy: 0.9400
6/40 [===>..........................] - ETA: 0s - loss: 0.1739 - accuracy: 0.9467
11/40 [=======>......................] - ETA: 0s - loss: 0.1810 - accuracy: 0.9445
17/40 [===========>..................] - ETA: 0s - loss: 0.1743 - accuracy: 0.9471
23/40 [================>.............] - ETA: 0s - loss: 0.1780 - accuracy: 0.9441
29/40 [====================>.........] - ETA: 0s - loss: 0.1715 - accuracy: 0.9478
35/40 [=========================>....] - ETA: 0s - loss: 0.1829 - accuracy: 0.9444
40/40 [==============================] - 0s 10ms/step - loss: 0.1873 - accuracy: 0.9429
40/40 [==============================] - 1s 14ms/step - loss: 0.1873 - accuracy: 0.9429 - val_loss: 1.1906 - val_accuracy: 0.7850
Epoch 7/30
1/40 [..............................] - ETA: 0s - loss: 0.1061 - accuracy: 0.9650
7/40 [====>.........................] - ETA: 0s - loss: 0.1439 - accuracy: 0.9507
13/40 [========>.....................] - ETA: 0s - loss: 0.1392 - accuracy: 0.9527
19/40 [=============>................] - ETA: 0s - loss: 0.1550 - accuracy: 0.9503
25/40 [=================>............] - ETA: 0s - loss: 0.1578 - accuracy: 0.9506
31/40 [======================>.......] - ETA: 0s - loss: 0.1521 - accuracy: 0.9523
37/40 [==========================>...] - ETA: 0s - loss: 0.1592 - accuracy: 0.9500
40/40 [==============================] - 0s 9ms/step - loss: 0.1635 - accuracy: 0.9486
40/40 [==============================] - 1s 13ms/step - loss: 0.1635 - accuracy: 0.9486 - val_loss: 1.1344 - val_accuracy: 0.7940
Epoch 8/30
1/40 [..............................] - ETA: 0s - loss: 0.0892 - accuracy: 0.9600
7/40 [====>.........................] - ETA: 0s - loss: 0.1186 - accuracy: 0.9543
13/40 [========>.....................] - ETA: 0s - loss: 0.1216 - accuracy: 0.9531
19/40 [=============>................] - ETA: 0s - loss: 0.1298 - accuracy: 0.9518
25/40 [=================>............] - ETA: 0s - loss: 0.1381 - accuracy: 0.9498
31/40 [======================>.......] - ETA: 0s - loss: 0.1330 - accuracy: 0.9510
37/40 [==========================>...] - ETA: 0s - loss: 0.1369 - accuracy: 0.9516
40/40 [==============================] - 0s 9ms/step - loss: 0.1398 - accuracy: 0.9513
40/40 [==============================] - 1s 13ms/step - loss: 0.1398 - accuracy: 0.9513 - val_loss: 1.2530 - val_accuracy: 0.7930
Epoch 9/30
1/40 [..............................] - ETA: 0s - loss: 0.1218 - accuracy: 0.9550
7/40 [====>.........................] - ETA: 0s - loss: 0.0906 - accuracy: 0.9679
13/40 [========>.....................] - ETA: 0s - loss: 0.1007 - accuracy: 0.9631
19/40 [=============>................] - ETA: 0s - loss: 0.1095 - accuracy: 0.9600
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40/40 [==============================] - 0s 9ms/step - loss: 0.1161 - accuracy: 0.9554
40/40 [==============================] - 1s 13ms/step - loss: 0.1161 - accuracy: 0.9554 - val_loss: 1.3765 - val_accuracy: 0.7870
Epoch 10/30
1/40 [..............................] - ETA: 0s - loss: 0.0858 - accuracy: 0.9550
7/40 [====>.........................] - ETA: 0s - loss: 0.1065 - accuracy: 0.9629
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40/40 [==============================] - 0s 9ms/step - loss: 0.1316 - accuracy: 0.9559
40/40 [==============================] - 1s 13ms/step - loss: 0.1316 - accuracy: 0.9559 - val_loss: 1.3795 - val_accuracy: 0.7970
Epoch 11/30
1/40 [..............................] - ETA: 0s - loss: 0.0946 - accuracy: 0.9600
7/40 [====>.........................] - ETA: 0s - loss: 0.0959 - accuracy: 0.9643
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31/40 [======================>.......] - ETA: 0s - loss: 0.1078 - accuracy: 0.9563
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40/40 [==============================] - 0s 9ms/step - loss: 0.1099 - accuracy: 0.9562
40/40 [==============================] - 1s 13ms/step - loss: 0.1099 - accuracy: 0.9562 - val_loss: 1.5007 - val_accuracy: 0.7870
Epoch 12/30
1/40 [..............................] - ETA: 0s - loss: 0.1465 - accuracy: 0.9350
7/40 [====>.........................] - ETA: 0s - loss: 0.0889 - accuracy: 0.9586
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19/40 [=============>................] - ETA: 0s - loss: 0.0937 - accuracy: 0.9597
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31/40 [======================>.......] - ETA: 0s - loss: 0.1013 - accuracy: 0.9590
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40/40 [==============================] - 0s 9ms/step - loss: 0.1036 - accuracy: 0.9572
40/40 [==============================] - 1s 13ms/step - loss: 0.1036 - accuracy: 0.9572 - val_loss: 1.4721 - val_accuracy: 0.7990
Epoch 13/30
1/40 [..............................] - ETA: 0s - loss: 0.0478 - accuracy: 0.9750
7/40 [====>.........................] - ETA: 0s - loss: 0.0591 - accuracy: 0.9736
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31/40 [======================>.......] - ETA: 0s - loss: 0.0959 - accuracy: 0.9618
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40/40 [==============================] - 0s 9ms/step - loss: 0.0979 - accuracy: 0.9593
40/40 [==============================] - 1s 13ms/step - loss: 0.0979 - accuracy: 0.9593 - val_loss: 1.6507 - val_accuracy: 0.7740
Epoch 14/30
1/40 [..............................] - ETA: 0s - loss: 0.0451 - accuracy: 0.9800
7/40 [====>.........................] - ETA: 0s - loss: 0.0782 - accuracy: 0.9693
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31/40 [======================>.......] - ETA: 0s - loss: 0.1074 - accuracy: 0.9579
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40/40 [==============================] - 0s 9ms/step - loss: 0.1120 - accuracy: 0.9559
40/40 [==============================] - 1s 13ms/step - loss: 0.1120 - accuracy: 0.9559 - val_loss: 1.5321 - val_accuracy: 0.7910
Epoch 15/30
1/40 [..............................] - ETA: 0s - loss: 0.0410 - accuracy: 0.9850
7/40 [====>.........................] - ETA: 0s - loss: 0.0920 - accuracy: 0.9693
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40/40 [==============================] - 0s 9ms/step - loss: 0.1190 - accuracy: 0.9567
40/40 [==============================] - 1s 13ms/step - loss: 0.1190 - accuracy: 0.9567 - val_loss: 1.6174 - val_accuracy: 0.7760
Epoch 16/30
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7/40 [====>.........................] - ETA: 0s - loss: 0.0926 - accuracy: 0.9686
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31/40 [======================>.......] - ETA: 0s - loss: 0.1186 - accuracy: 0.9558
37/40 [==========================>...] - ETA: 0s - loss: 0.1228 - accuracy: 0.9550
40/40 [==============================] - 0s 9ms/step - loss: 0.1242 - accuracy: 0.9541
40/40 [==============================] - 1s 13ms/step - loss: 0.1242 - accuracy: 0.9541 - val_loss: 1.5874 - val_accuracy: 0.7880
Epoch 17/30
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31/40 [======================>.......] - ETA: 0s - loss: 0.1176 - accuracy: 0.9569
37/40 [==========================>...] - ETA: 0s - loss: 0.1282 - accuracy: 0.9534
40/40 [==============================] - 0s 9ms/step - loss: 0.1319 - accuracy: 0.9523
40/40 [==============================] - 1s 13ms/step - loss: 0.1319 - accuracy: 0.9523 - val_loss: 1.5827 - val_accuracy: 0.7910
Epoch 18/30
1/40 [..............................] - ETA: 0s - loss: 0.0793 - accuracy: 0.9650
7/40 [====>.........................] - ETA: 0s - loss: 0.1130 - accuracy: 0.9600
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31/40 [======================>.......] - ETA: 0s - loss: 0.1208 - accuracy: 0.9561
37/40 [==========================>...] - ETA: 0s - loss: 0.1347 - accuracy: 0.9542
40/40 [==============================] - 0s 9ms/step - loss: 0.1377 - accuracy: 0.9534
40/40 [==============================] - 1s 13ms/step - loss: 0.1377 - accuracy: 0.9534 - val_loss: 1.6651 - val_accuracy: 0.7920
Epoch 19/30
1/40 [..............................] - ETA: 0s - loss: 0.1226 - accuracy: 0.9400
7/40 [====>.........................] - ETA: 0s - loss: 0.1248 - accuracy: 0.9521
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31/40 [======================>.......] - ETA: 0s - loss: 0.1409 - accuracy: 0.9542
37/40 [==========================>...] - ETA: 0s - loss: 0.1463 - accuracy: 0.9522
40/40 [==============================] - 0s 9ms/step - loss: 0.1497 - accuracy: 0.9516
40/40 [==============================] - 1s 22ms/step - loss: 0.1497 - accuracy: 0.9516 - val_loss: 2.1278 - val_accuracy: 0.7880
Epoch 20/30
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7/40 [====>.........................] - ETA: 0s - loss: 0.1300 - accuracy: 0.9586
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31/40 [======================>.......] - ETA: 0s - loss: 0.1537 - accuracy: 0.9534
37/40 [==========================>...] - ETA: 0s - loss: 0.1593 - accuracy: 0.9518
40/40 [==============================] - 0s 9ms/step - loss: 0.1622 - accuracy: 0.9510
40/40 [==============================] - 1s 13ms/step - loss: 0.1622 - accuracy: 0.9510 - val_loss: 1.7350 - val_accuracy: 0.7900
Epoch 21/30
1/40 [..............................] - ETA: 0s - loss: 0.1895 - accuracy: 0.9450
7/40 [====>.........................] - ETA: 0s - loss: 0.1341 - accuracy: 0.9536
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31/40 [======================>.......] - ETA: 0s - loss: 0.1434 - accuracy: 0.9519
37/40 [==========================>...] - ETA: 0s - loss: 0.1437 - accuracy: 0.9503
40/40 [==============================] - 0s 9ms/step - loss: 0.1464 - accuracy: 0.9491
40/40 [==============================] - 1s 14ms/step - loss: 0.1464 - accuracy: 0.9491 - val_loss: 2.2689 - val_accuracy: 0.7760
Epoch 22/30
1/40 [..............................] - ETA: 0s - loss: 0.1078 - accuracy: 0.9700
6/40 [===>..........................] - ETA: 0s - loss: 0.1244 - accuracy: 0.9575
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29/40 [====================>.........] - ETA: 0s - loss: 0.1584 - accuracy: 0.9510
35/40 [=========================>....] - ETA: 0s - loss: 0.1586 - accuracy: 0.9517
40/40 [==============================] - 0s 10ms/step - loss: 0.1573 - accuracy: 0.9511
40/40 [==============================] - 1s 14ms/step - loss: 0.1573 - accuracy: 0.9511 - val_loss: 2.2208 - val_accuracy: 0.7710
Epoch 23/30
1/40 [..............................] - ETA: 0s - loss: 0.1024 - accuracy: 0.9700
7/40 [====>.........................] - ETA: 0s - loss: 0.1363 - accuracy: 0.9514
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19/40 [=============>................] - ETA: 0s - loss: 0.1582 - accuracy: 0.9479
25/40 [=================>............] - ETA: 0s - loss: 0.1563 - accuracy: 0.9470
30/40 [=====================>........] - ETA: 0s - loss: 0.1699 - accuracy: 0.9458
35/40 [=========================>....] - ETA: 0s - loss: 0.1821 - accuracy: 0.9441
40/40 [==============================] - 0s 9ms/step - loss: 0.1759 - accuracy: 0.9451
40/40 [==============================] - 1s 14ms/step - loss: 0.1759 - accuracy: 0.9451 - val_loss: 2.0922 - val_accuracy: 0.7760
Epoch 24/30
1/40 [..............................] - ETA: 0s - loss: 0.2059 - accuracy: 0.9450
6/40 [===>..........................] - ETA: 0s - loss: 0.1721 - accuracy: 0.9408
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18/40 [============>.................] - ETA: 0s - loss: 0.1672 - accuracy: 0.9497
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28/40 [====================>.........] - ETA: 0s - loss: 0.1636 - accuracy: 0.9511
33/40 [=======================>......] - ETA: 0s - loss: 0.1723 - accuracy: 0.9494
38/40 [===========================>..] - ETA: 0s - loss: 0.1823 - accuracy: 0.9467
40/40 [==============================] - 0s 10ms/step - loss: 0.1836 - accuracy: 0.9460
40/40 [==============================] - 1s 14ms/step - loss: 0.1836 - accuracy: 0.9460 - val_loss: 2.2042 - val_accuracy: 0.7700
Epoch 25/30
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7/40 [====>.........................] - ETA: 0s - loss: 0.2094 - accuracy: 0.9514
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19/40 [=============>................] - ETA: 0s - loss: 0.1777 - accuracy: 0.9553
24/40 [=================>............] - ETA: 0s - loss: 0.1871 - accuracy: 0.9515
29/40 [====================>.........] - ETA: 0s - loss: 0.1862 - accuracy: 0.9497
34/40 [========================>.....] - ETA: 0s - loss: 0.1982 - accuracy: 0.9476
39/40 [============================>.] - ETA: 0s - loss: 0.1975 - accuracy: 0.9467
40/40 [==============================] - 0s 10ms/step - loss: 0.1968 - accuracy: 0.9465
40/40 [==============================] - 1s 14ms/step - loss: 0.1968 - accuracy: 0.9465 - val_loss: 2.0375 - val_accuracy: 0.7700
Epoch 26/30
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6/40 [===>..........................] - ETA: 0s - loss: 0.1019 - accuracy: 0.9608
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31/40 [======================>.......] - ETA: 0s - loss: 0.1756 - accuracy: 0.9498
36/40 [==========================>...] - ETA: 0s - loss: 0.1765 - accuracy: 0.9501
40/40 [==============================] - 0s 10ms/step - loss: 0.1781 - accuracy: 0.9485
40/40 [==============================] - 1s 15ms/step - loss: 0.1781 - accuracy: 0.9485 - val_loss: 2.3790 - val_accuracy: 0.7830
Epoch 27/30
1/40 [..............................] - ETA: 0s - loss: 0.1296 - accuracy: 0.9450
6/40 [===>..........................] - ETA: 0s - loss: 0.1575 - accuracy: 0.9492
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16/40 [===========>..................] - ETA: 0s - loss: 0.1665 - accuracy: 0.9522
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27/40 [===================>..........] - ETA: 0s - loss: 0.1773 - accuracy: 0.9533
32/40 [=======================>......] - ETA: 0s - loss: 0.1775 - accuracy: 0.9530
37/40 [==========================>...] - ETA: 0s - loss: 0.1836 - accuracy: 0.9505
40/40 [==============================] - 0s 10ms/step - loss: 0.1818 - accuracy: 0.9500
40/40 [==============================] - 1s 14ms/step - loss: 0.1818 - accuracy: 0.9500 - val_loss: 2.1716 - val_accuracy: 0.7770
Epoch 28/30
1/40 [..............................] - ETA: 0s - loss: 0.1109 - accuracy: 0.9550
6/40 [===>..........................] - ETA: 0s - loss: 0.1029 - accuracy: 0.9608
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18/40 [============>.................] - ETA: 0s - loss: 0.1206 - accuracy: 0.9567
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28/40 [====================>.........] - ETA: 0s - loss: 0.1232 - accuracy: 0.9545
33/40 [=======================>......] - ETA: 0s - loss: 0.1349 - accuracy: 0.9526
38/40 [===========================>..] - ETA: 0s - loss: 0.1364 - accuracy: 0.9532
40/40 [==============================] - 0s 10ms/step - loss: 0.1366 - accuracy: 0.9530
40/40 [==============================] - 1s 15ms/step - loss: 0.1366 - accuracy: 0.9530 - val_loss: 2.3011 - val_accuracy: 0.7800
Epoch 29/30
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6/40 [===>..........................] - ETA: 0s - loss: 0.1414 - accuracy: 0.9508
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16/40 [===========>..................] - ETA: 0s - loss: 0.1445 - accuracy: 0.9531
21/40 [==============>...............] - ETA: 0s - loss: 0.1500 - accuracy: 0.9533
26/40 [==================>...........] - ETA: 0s - loss: 0.1535 - accuracy: 0.9504
31/40 [======================>.......] - ETA: 0s - loss: 0.1479 - accuracy: 0.9506
36/40 [==========================>...] - ETA: 0s - loss: 0.1485 - accuracy: 0.9513
40/40 [==============================] - 0s 11ms/step - loss: 0.1451 - accuracy: 0.9521
40/40 [==============================] - 1s 15ms/step - loss: 0.1451 - accuracy: 0.9521 - val_loss: 2.7052 - val_accuracy: 0.7870
Epoch 30/30
1/40 [..............................] - ETA: 0s - loss: 0.0606 - accuracy: 0.9800
6/40 [===>..........................] - ETA: 0s - loss: 0.1108 - accuracy: 0.9600
11/40 [=======>......................] - ETA: 0s - loss: 0.1036 - accuracy: 0.9609
16/40 [===========>..................] - ETA: 0s - loss: 0.1018 - accuracy: 0.9584
21/40 [==============>...............] - ETA: 0s - loss: 0.1090 - accuracy: 0.9586
26/40 [==================>...........] - ETA: 0s - loss: 0.1147 - accuracy: 0.9575
31/40 [======================>.......] - ETA: 0s - loss: 0.1181 - accuracy: 0.9565
36/40 [==========================>...] - ETA: 0s - loss: 0.1245 - accuracy: 0.9554
40/40 [==============================] - 0s 11ms/step - loss: 0.1280 - accuracy: 0.9541
40/40 [==============================] - 1s 15ms/step - loss: 0.1280 - accuracy: 0.9541 - val_loss: 2.5484 - val_accuracy: 0.7700
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-16-38Z
Training run 4/8 (flags = list(392, 0.01, 100, 50, "sigmoid"))
Using run directory runs/2020-11-02T21-16-58Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/50
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17/80 [=====>........................] - ETA: 0s - loss: 3.0245 - accuracy: 0.2935
20/80 [======>.......................] - ETA: 0s - loss: 2.9250 - accuracy: 0.3220
24/80 [========>.....................] - ETA: 0s - loss: 2.8071 - accuracy: 0.3475
28/80 [=========>....................] - ETA: 0s - loss: 2.6994 - accuracy: 0.3743
32/80 [===========>..................] - ETA: 0s - loss: 2.6154 - accuracy: 0.3906
36/80 [============>.................] - ETA: 0s - loss: 2.5232 - accuracy: 0.4097
39/80 [=============>................] - ETA: 0s - loss: 2.4508 - accuracy: 0.4238
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78/80 [============================>.] - ETA: 0s - loss: 2.0473 - accuracy: 0.4974
80/80 [==============================] - 1s 16ms/step - loss: 2.0361 - accuracy: 0.4990
80/80 [==============================] - 2s 25ms/step - loss: 2.0361 - accuracy: 0.4990 - val_loss: 1.4736 - val_accuracy: 0.6100
Epoch 2/50
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5/80 [>.............................] - ETA: 0s - loss: 1.3147 - accuracy: 0.6520
9/80 [==>...........................] - ETA: 0s - loss: 1.3559 - accuracy: 0.6456
13/80 [===>..........................] - ETA: 0s - loss: 1.3266 - accuracy: 0.6554
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21/80 [======>.......................] - ETA: 0s - loss: 1.2950 - accuracy: 0.6671
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33/80 [===========>..................] - ETA: 0s - loss: 1.2772 - accuracy: 0.6736
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80/80 [==============================] - 1s 16ms/step - loss: 1.1776 - accuracy: 0.7080
80/80 [==============================] - 1s 18ms/step - loss: 1.1776 - accuracy: 0.7080 - val_loss: 1.1140 - val_accuracy: 0.7170
Epoch 3/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.7816 - accuracy: 0.8067
80/80 [==============================] - 2s 19ms/step - loss: 0.7816 - accuracy: 0.8067 - val_loss: 1.0283 - val_accuracy: 0.7460
Epoch 4/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.5620 - accuracy: 0.8566
80/80 [==============================] - 2s 20ms/step - loss: 0.5620 - accuracy: 0.8566 - val_loss: 0.9676 - val_accuracy: 0.7690
Epoch 5/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.4017 - accuracy: 0.8974
80/80 [==============================] - 2s 20ms/step - loss: 0.4017 - accuracy: 0.8974 - val_loss: 1.0019 - val_accuracy: 0.7740
Epoch 6/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.2953 - accuracy: 0.9221
80/80 [==============================] - 2s 20ms/step - loss: 0.2953 - accuracy: 0.9221 - val_loss: 1.1097 - val_accuracy: 0.7770
Epoch 7/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.2348 - accuracy: 0.9341
80/80 [==============================] - 2s 20ms/step - loss: 0.2348 - accuracy: 0.9341 - val_loss: 1.2123 - val_accuracy: 0.7740
Epoch 8/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.1970 - accuracy: 0.9446
80/80 [==============================] - 2s 20ms/step - loss: 0.1970 - accuracy: 0.9446 - val_loss: 1.1621 - val_accuracy: 0.7730
Epoch 9/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.1577 - accuracy: 0.9523
80/80 [==============================] - 2s 20ms/step - loss: 0.1577 - accuracy: 0.9523 - val_loss: 1.1753 - val_accuracy: 0.7890
Epoch 10/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.1391 - accuracy: 0.9541
80/80 [==============================] - 2s 20ms/step - loss: 0.1391 - accuracy: 0.9541 - val_loss: 1.3592 - val_accuracy: 0.7810
Epoch 11/50
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80/80 [==============================] - 1s 18ms/step - loss: 0.1202 - accuracy: 0.9580
80/80 [==============================] - 2s 20ms/step - loss: 0.1202 - accuracy: 0.9580 - val_loss: 1.3910 - val_accuracy: 0.7680
Epoch 12/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.1162 - accuracy: 0.9565
80/80 [==============================] - 2s 20ms/step - loss: 0.1162 - accuracy: 0.9565 - val_loss: 1.3487 - val_accuracy: 0.7910
Epoch 13/50
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80/80 [==============================] - 1s 17ms/step - loss: 0.1058 - accuracy: 0.9584
80/80 [==============================] - 2s 20ms/step - loss: 0.1058 - accuracy: 0.9584 - val_loss: 1.4024 - val_accuracy: 0.7790
Epoch 14/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.1010 - accuracy: 0.9597
80/80 [==============================] - 2s 19ms/step - loss: 0.1010 - accuracy: 0.9597 - val_loss: 1.5769 - val_accuracy: 0.7870
Epoch 15/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0937 - accuracy: 0.9612
80/80 [==============================] - 1s 18ms/step - loss: 0.0937 - accuracy: 0.9612 - val_loss: 1.4984 - val_accuracy: 0.7740
Epoch 16/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0918 - accuracy: 0.9604
80/80 [==============================] - 1s 18ms/step - loss: 0.0918 - accuracy: 0.9604 - val_loss: 1.5181 - val_accuracy: 0.7780
Epoch 17/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0902 - accuracy: 0.9595
80/80 [==============================] - 1s 18ms/step - loss: 0.0902 - accuracy: 0.9595 - val_loss: 1.6127 - val_accuracy: 0.7800
Epoch 18/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0922 - accuracy: 0.9599
80/80 [==============================] - 1s 18ms/step - loss: 0.0922 - accuracy: 0.9599 - val_loss: 1.5113 - val_accuracy: 0.7800
Epoch 19/50
1/80 [..............................] - ETA: 0s - loss: 0.0477 - accuracy: 0.9900
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80/80 [==============================] - 1s 15ms/step - loss: 0.0842 - accuracy: 0.9619
80/80 [==============================] - 1s 17ms/step - loss: 0.0842 - accuracy: 0.9619 - val_loss: 1.5294 - val_accuracy: 0.7900
Epoch 20/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0822 - accuracy: 0.9612
80/80 [==============================] - 1s 18ms/step - loss: 0.0822 - accuracy: 0.9612 - val_loss: 1.4845 - val_accuracy: 0.7800
Epoch 21/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0805 - accuracy: 0.9623
80/80 [==============================] - 1s 17ms/step - loss: 0.0805 - accuracy: 0.9623 - val_loss: 1.5515 - val_accuracy: 0.7720
Epoch 22/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0806 - accuracy: 0.9602
80/80 [==============================] - 1s 18ms/step - loss: 0.0806 - accuracy: 0.9602 - val_loss: 1.6303 - val_accuracy: 0.7800
Epoch 23/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0792 - accuracy: 0.9607
80/80 [==============================] - 1s 17ms/step - loss: 0.0792 - accuracy: 0.9607 - val_loss: 1.5756 - val_accuracy: 0.7790
Epoch 24/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0791 - accuracy: 0.9592
80/80 [==============================] - 1s 17ms/step - loss: 0.0791 - accuracy: 0.9592 - val_loss: 1.6143 - val_accuracy: 0.7940
Epoch 25/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0735 - accuracy: 0.9618
80/80 [==============================] - 1s 18ms/step - loss: 0.0735 - accuracy: 0.9618 - val_loss: 1.7155 - val_accuracy: 0.7960
Epoch 26/50
1/80 [..............................] - ETA: 0s - loss: 0.0371 - accuracy: 0.9800
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80/80 [==============================] - 1s 15ms/step - loss: 0.0729 - accuracy: 0.9619
80/80 [==============================] - 1s 18ms/step - loss: 0.0729 - accuracy: 0.9619 - val_loss: 1.6061 - val_accuracy: 0.7720
Epoch 27/50
1/80 [..............................] - ETA: 0s - loss: 0.0639 - accuracy: 0.9700
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80/80 [==============================] - 1s 15ms/step - loss: 0.0720 - accuracy: 0.9619
80/80 [==============================] - 1s 18ms/step - loss: 0.0720 - accuracy: 0.9619 - val_loss: 1.7233 - val_accuracy: 0.7810
Epoch 28/50
1/80 [..............................] - ETA: 0s - loss: 0.0398 - accuracy: 0.9900
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80/80 [==============================] - 1s 16ms/step - loss: 0.0712 - accuracy: 0.9620
80/80 [==============================] - 1s 18ms/step - loss: 0.0712 - accuracy: 0.9620 - val_loss: 1.6795 - val_accuracy: 0.7730
Epoch 29/50
1/80 [..............................] - ETA: 0s - loss: 0.0723 - accuracy: 0.9700
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80/80 [==============================] - 1s 16ms/step - loss: 0.0720 - accuracy: 0.9627
80/80 [==============================] - 1s 18ms/step - loss: 0.0720 - accuracy: 0.9627 - val_loss: 1.6656 - val_accuracy: 0.7880
Epoch 30/50
1/80 [..............................] - ETA: 0s - loss: 0.0646 - accuracy: 0.9800
5/80 [>.............................] - ETA: 0s - loss: 0.0811 - accuracy: 0.9580
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80/80 [==============================] - 1s 15ms/step - loss: 0.0707 - accuracy: 0.9625
80/80 [==============================] - 1s 18ms/step - loss: 0.0707 - accuracy: 0.9625 - val_loss: 1.6614 - val_accuracy: 0.7820
Epoch 31/50
1/80 [..............................] - ETA: 0s - loss: 0.0193 - accuracy: 1.0000
5/80 [>.............................] - ETA: 0s - loss: 0.0257 - accuracy: 0.9880
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80/80 [==============================] - 1s 15ms/step - loss: 0.0719 - accuracy: 0.9615
80/80 [==============================] - 1s 18ms/step - loss: 0.0719 - accuracy: 0.9615 - val_loss: 1.7947 - val_accuracy: 0.7910
Epoch 32/50
1/80 [..............................] - ETA: 0s - loss: 0.0444 - accuracy: 0.9900
5/80 [>.............................] - ETA: 0s - loss: 0.0705 - accuracy: 0.9720
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80/80 [==============================] - 1s 15ms/step - loss: 0.0710 - accuracy: 0.9595
80/80 [==============================] - 1s 18ms/step - loss: 0.0710 - accuracy: 0.9595 - val_loss: 1.8373 - val_accuracy: 0.7930
Epoch 33/50
1/80 [..............................] - ETA: 0s - loss: 0.0396 - accuracy: 0.9700
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80/80 [==============================] - 1s 15ms/step - loss: 0.0673 - accuracy: 0.9600
80/80 [==============================] - 1s 18ms/step - loss: 0.0673 - accuracy: 0.9600 - val_loss: 1.8260 - val_accuracy: 0.7900
Epoch 34/50
1/80 [..............................] - ETA: 0s - loss: 0.0304 - accuracy: 0.9800
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80/80 [==============================] - 1s 16ms/step - loss: 0.0708 - accuracy: 0.9608
80/80 [==============================] - 1s 19ms/step - loss: 0.0708 - accuracy: 0.9608 - val_loss: 1.7518 - val_accuracy: 0.7850
Epoch 35/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0664 - accuracy: 0.9617
80/80 [==============================] - 1s 18ms/step - loss: 0.0664 - accuracy: 0.9617 - val_loss: 1.8664 - val_accuracy: 0.7870
Epoch 36/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0679 - accuracy: 0.9615
80/80 [==============================] - 1s 18ms/step - loss: 0.0679 - accuracy: 0.9615 - val_loss: 1.7939 - val_accuracy: 0.7750
Epoch 37/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0687 - accuracy: 0.9612
80/80 [==============================] - 1s 18ms/step - loss: 0.0687 - accuracy: 0.9612 - val_loss: 1.7947 - val_accuracy: 0.7890
Epoch 38/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0706 - accuracy: 0.9627
80/80 [==============================] - 1s 17ms/step - loss: 0.0706 - accuracy: 0.9627 - val_loss: 1.7733 - val_accuracy: 0.7720
Epoch 39/50
1/80 [..............................] - ETA: 0s - loss: 0.0725 - accuracy: 0.9600
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80/80 [==============================] - 1s 15ms/step - loss: 0.0713 - accuracy: 0.9608
80/80 [==============================] - 1s 18ms/step - loss: 0.0713 - accuracy: 0.9608 - val_loss: 1.9409 - val_accuracy: 0.7880
Epoch 40/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0721 - accuracy: 0.9619
80/80 [==============================] - 1s 17ms/step - loss: 0.0721 - accuracy: 0.9619 - val_loss: 1.8386 - val_accuracy: 0.7780
Epoch 41/50
1/80 [..............................] - ETA: 0s - loss: 0.1098 - accuracy: 0.9500
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80/80 [==============================] - 1s 15ms/step - loss: 0.0989 - accuracy: 0.9528
80/80 [==============================] - 1s 17ms/step - loss: 0.0989 - accuracy: 0.9528 - val_loss: 1.7513 - val_accuracy: 0.7610
Epoch 42/50
1/80 [..............................] - ETA: 0s - loss: 0.0724 - accuracy: 0.9700
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80/80 [==============================] - 1s 15ms/step - loss: 0.1685 - accuracy: 0.9397
80/80 [==============================] - 1s 18ms/step - loss: 0.1685 - accuracy: 0.9397 - val_loss: 1.4359 - val_accuracy: 0.7740
Epoch 43/50
1/80 [..............................] - ETA: 0s - loss: 0.1402 - accuracy: 0.9500
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80/80 [==============================] - 1s 15ms/step - loss: 0.1433 - accuracy: 0.9474
80/80 [==============================] - 1s 17ms/step - loss: 0.1433 - accuracy: 0.9474 - val_loss: 1.4991 - val_accuracy: 0.7820
Epoch 44/50
1/80 [..............................] - ETA: 0s - loss: 0.0797 - accuracy: 0.9700
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80/80 [==============================] - 1s 15ms/step - loss: 0.1109 - accuracy: 0.9553
80/80 [==============================] - 1s 18ms/step - loss: 0.1109 - accuracy: 0.9553 - val_loss: 1.6398 - val_accuracy: 0.7850
Epoch 45/50
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80/80 [==============================] - 1s 15ms/step - loss: 0.0920 - accuracy: 0.9582
80/80 [==============================] - 1s 18ms/step - loss: 0.0920 - accuracy: 0.9582 - val_loss: 1.6380 - val_accuracy: 0.7780
Epoch 46/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0809 - accuracy: 0.9609
80/80 [==============================] - 1s 18ms/step - loss: 0.0809 - accuracy: 0.9609 - val_loss: 1.6501 - val_accuracy: 0.7720
Epoch 47/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0750 - accuracy: 0.9608
80/80 [==============================] - 1s 18ms/step - loss: 0.0750 - accuracy: 0.9608 - val_loss: 1.6649 - val_accuracy: 0.7840
Epoch 48/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0702 - accuracy: 0.9607
80/80 [==============================] - 1s 19ms/step - loss: 0.0702 - accuracy: 0.9607 - val_loss: 1.7457 - val_accuracy: 0.7860
Epoch 49/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0659 - accuracy: 0.9599
80/80 [==============================] - 1s 18ms/step - loss: 0.0659 - accuracy: 0.9599 - val_loss: 1.7895 - val_accuracy: 0.7840
Epoch 50/50
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80/80 [==============================] - 1s 16ms/step - loss: 0.0633 - accuracy: 0.9634
80/80 [==============================] - 1s 19ms/step - loss: 0.0633 - accuracy: 0.9634 - val_loss: 1.8450 - val_accuracy: 0.7860
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-16-58Z
Training run 5/8 (flags = list(392, 0.05, 1000, 100, "tanh"))
Using run directory runs/2020-11-02T21-18-15Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/100
1/8 [==>...........................] - ETA: 0s - loss: 3.8417 - accuracy: 0.0160
2/8 [======>.......................] - ETA: 0s - loss: 5.6983 - accuracy: 0.1800
3/8 [==========>...................] - ETA: 0s - loss: 7.5603 - accuracy: 0.1380
4/8 [==============>...............] - ETA: 0s - loss: 7.6880 - accuracy: 0.1045
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6/8 [=====================>........] - ETA: 0s - loss: 8.2909 - accuracy: 0.1078
7/8 [=========================>....] - ETA: 0s - loss: 9.5100 - accuracy: 0.1414
8/8 [==============================] - 1s 70ms/step - loss: 10.7742 - accuracy: 0.1253
8/8 [==============================] - 1s 155ms/step - loss: 10.7742 - accuracy: 0.1253 - val_loss: 22.8716 - val_accuracy: 0.0440
Epoch 2/100
1/8 [==>...........................] - ETA: 0s - loss: 22.2717 - accuracy: 0.0450
2/8 [======>.......................] - ETA: 0s - loss: 22.4474 - accuracy: 0.0240
3/8 [==========>...................] - ETA: 0s - loss: 23.7851 - accuracy: 0.0160
4/8 [==============>...............] - ETA: 0s - loss: 24.6656 - accuracy: 0.0262
5/8 [=================>............] - ETA: 0s - loss: 25.1456 - accuracy: 0.0228
6/8 [=====================>........] - ETA: 0s - loss: 25.8229 - accuracy: 0.0772
7/8 [=========================>....] - ETA: 0s - loss: 26.9578 - accuracy: 0.0734
8/8 [==============================] - 1s 67ms/step - loss: 27.5317 - accuracy: 0.0654
8/8 [==============================] - 1s 89ms/step - loss: 27.5317 - accuracy: 0.0654 - val_loss: 35.3418 - val_accuracy: 0.0030
Epoch 3/100
1/8 [==>...........................] - ETA: 0s - loss: 33.1896 - accuracy: 0.0060
2/8 [======>.......................] - ETA: 0s - loss: 34.4146 - accuracy: 0.0065
3/8 [==========>...................] - ETA: 0s - loss: 35.9582 - accuracy: 0.1237
4/8 [==============>...............] - ETA: 0s - loss: 37.5180 - accuracy: 0.0935
5/8 [=================>............] - ETA: 0s - loss: 38.8406 - accuracy: 0.1160
6/8 [=====================>........] - ETA: 0s - loss: 39.6907 - accuracy: 0.1563
7/8 [=========================>....] - ETA: 0s - loss: 40.6560 - accuracy: 0.1363
8/8 [==============================] - 1s 65ms/step - loss: 41.7346 - accuracy: 0.1199
8/8 [==============================] - 1s 88ms/step - loss: 41.7346 - accuracy: 0.1199 - val_loss: 46.9073 - val_accuracy: 0.0100
Epoch 4/100
1/8 [==>...........................] - ETA: 0s - loss: 50.8773 - accuracy: 0.0100
2/8 [======>.......................] - ETA: 0s - loss: 48.6806 - accuracy: 0.1160
3/8 [==========>...................] - ETA: 0s - loss: 47.8881 - accuracy: 0.1970
4/8 [==============>...............] - ETA: 0s - loss: 47.5237 - accuracy: 0.2412
5/8 [=================>............] - ETA: 0s - loss: 48.1851 - accuracy: 0.1934
6/8 [=====================>........] - ETA: 0s - loss: 47.3972 - accuracy: 0.2178
7/8 [=========================>....] - ETA: 0s - loss: 46.7904 - accuracy: 0.2186
8/8 [==============================] - 1s 67ms/step - loss: 46.4306 - accuracy: 0.1924
8/8 [==============================] - 1s 88ms/step - loss: 46.4306 - accuracy: 0.1924 - val_loss: 48.1292 - val_accuracy: 0.0170
Epoch 5/100
1/8 [==>...........................] - ETA: 0s - loss: 46.6728 - accuracy: 0.0160
2/8 [======>.......................] - ETA: 0s - loss: 46.6549 - accuracy: 0.0195
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4/8 [==============>...............] - ETA: 0s - loss: 44.4159 - accuracy: 0.0953
5/8 [=================>............] - ETA: 0s - loss: 43.1060 - accuracy: 0.1506
6/8 [=====================>........] - ETA: 0s - loss: 42.5246 - accuracy: 0.1258
7/8 [=========================>....] - ETA: 0s - loss: 42.6250 - accuracy: 0.1387
8/8 [==============================] - 1s 68ms/step - loss: 42.4152 - accuracy: 0.1466
8/8 [==============================] - 1s 90ms/step - loss: 42.4152 - accuracy: 0.1466 - val_loss: 41.7190 - val_accuracy: 0.0030
Epoch 6/100
1/8 [==>...........................] - ETA: 0s - loss: 41.7416 - accuracy: 0.0040
2/8 [======>.......................] - ETA: 0s - loss: 39.0167 - accuracy: 0.1820
3/8 [==========>...................] - ETA: 0s - loss: 38.0072 - accuracy: 0.2420
4/8 [==============>...............] - ETA: 0s - loss: 36.7395 - accuracy: 0.2713
5/8 [=================>............] - ETA: 0s - loss: 35.4415 - accuracy: 0.2894
6/8 [=====================>........] - ETA: 0s - loss: 33.7752 - accuracy: 0.2750
7/8 [=========================>....] - ETA: 0s - loss: 32.0177 - accuracy: 0.2694
8/8 [==============================] - 1s 70ms/step - loss: 30.8869 - accuracy: 0.2364
8/8 [==============================] - 1s 93ms/step - loss: 30.8869 - accuracy: 0.2364 - val_loss: 27.8603 - val_accuracy: 0.0590
Epoch 7/100
1/8 [==>...........................] - ETA: 0s - loss: 26.3668 - accuracy: 0.0490
2/8 [======>.......................] - ETA: 0s - loss: 26.1314 - accuracy: 0.0545
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4/8 [==============>...............] - ETA: 0s - loss: 27.3758 - accuracy: 0.1177
5/8 [=================>............] - ETA: 0s - loss: 26.8876 - accuracy: 0.1674
6/8 [=====================>........] - ETA: 0s - loss: 27.0468 - accuracy: 0.1983
7/8 [=========================>....] - ETA: 0s - loss: 26.5625 - accuracy: 0.2209
8/8 [==============================] - 1s 73ms/step - loss: 26.0670 - accuracy: 0.1992
8/8 [==============================] - 1s 95ms/step - loss: 26.0670 - accuracy: 0.1992 - val_loss: 26.3622 - val_accuracy: 0.2220
Epoch 8/100
1/8 [==>...........................] - ETA: 0s - loss: 26.5924 - accuracy: 0.2060
2/8 [======>.......................] - ETA: 0s - loss: 26.4438 - accuracy: 0.2020
3/8 [==========>...................] - ETA: 0s - loss: 25.5564 - accuracy: 0.1547
4/8 [==============>...............] - ETA: 0s - loss: 24.2571 - accuracy: 0.1315
5/8 [=================>............] - ETA: 0s - loss: 22.8175 - accuracy: 0.1812
6/8 [=====================>........] - ETA: 0s - loss: 22.4633 - accuracy: 0.2093
7/8 [=========================>....] - ETA: 0s - loss: 21.8593 - accuracy: 0.2304
8/8 [==============================] - 1s 76ms/step - loss: 21.4770 - accuracy: 0.2279
8/8 [==============================] - 1s 98ms/step - loss: 21.4770 - accuracy: 0.2279 - val_loss: 17.5766 - val_accuracy: 0.0250
Epoch 9/100
1/8 [==>...........................] - ETA: 0s - loss: 16.9451 - accuracy: 0.0290
2/8 [======>.......................] - ETA: 0s - loss: 16.7080 - accuracy: 0.0380
3/8 [==========>...................] - ETA: 0s - loss: 17.6069 - accuracy: 0.0420
4/8 [==============>...............] - ETA: 0s - loss: 17.3064 - accuracy: 0.1217
5/8 [=================>............] - ETA: 0s - loss: 16.7440 - accuracy: 0.1704
6/8 [=====================>........] - ETA: 0s - loss: 16.9704 - accuracy: 0.1440
7/8 [=========================>....] - ETA: 0s - loss: 17.3169 - accuracy: 0.1556
8/8 [==============================] - 1s 75ms/step - loss: 17.4214 - accuracy: 0.1773
8/8 [==============================] - 1s 98ms/step - loss: 17.4214 - accuracy: 0.1773 - val_loss: 17.1302 - val_accuracy: 0.3540
Epoch 10/100
1/8 [==>...........................] - ETA: 0s - loss: 15.9388 - accuracy: 0.3560
2/8 [======>.......................] - ETA: 0s - loss: 15.8878 - accuracy: 0.3570
3/8 [==========>...................] - ETA: 0s - loss: 14.9138 - accuracy: 0.3093
4/8 [==============>...............] - ETA: 0s - loss: 14.8348 - accuracy: 0.2865
5/8 [=================>............] - ETA: 0s - loss: 14.7423 - accuracy: 0.2316
6/8 [=====================>........] - ETA: 0s - loss: 14.4709 - accuracy: 0.2512
7/8 [=========================>....] - ETA: 0s - loss: 14.2219 - accuracy: 0.2241
8/8 [==============================] - 1s 75ms/step - loss: 13.8628 - accuracy: 0.2398
8/8 [==============================] - 1s 98ms/step - loss: 13.8628 - accuracy: 0.2398 - val_loss: 11.0338 - val_accuracy: 0.3540
Epoch 11/100
1/8 [==>...........................] - ETA: 0s - loss: 11.5511 - accuracy: 0.3580
2/8 [======>.......................] - ETA: 0s - loss: 11.5966 - accuracy: 0.2835
3/8 [==========>...................] - ETA: 0s - loss: 11.2783 - accuracy: 0.3040
4/8 [==============>...............] - ETA: 0s - loss: 10.9875 - accuracy: 0.3205
5/8 [=================>............] - ETA: 0s - loss: 11.0793 - accuracy: 0.2616
6/8 [=====================>........] - ETA: 0s - loss: 10.9717 - accuracy: 0.2758
7/8 [=========================>....] - ETA: 0s - loss: 10.8461 - accuracy: 0.2684
8/8 [==============================] - 1s 81ms/step - loss: 10.7455 - accuracy: 0.2612
8/8 [==============================] - 1s 105ms/step - loss: 10.7455 - accuracy: 0.2612 - val_loss: 10.1811 - val_accuracy: 0.3540
Epoch 12/100
1/8 [==>...........................] - ETA: 0s - loss: 9.5264 - accuracy: 0.3590
2/8 [======>.......................] - ETA: 0s - loss: 10.2035 - accuracy: 0.3465
3/8 [==========>...................] - ETA: 0s - loss: 10.1411 - accuracy: 0.3537
4/8 [==============>...............] - ETA: 0s - loss: 10.1646 - accuracy: 0.3178
5/8 [=================>............] - ETA: 0s - loss: 10.1260 - accuracy: 0.3252
6/8 [=====================>........] - ETA: 0s - loss: 9.9486 - accuracy: 0.3278
7/8 [=========================>....] - ETA: 0s - loss: 9.8705 - accuracy: 0.3290
8/8 [==============================] - 1s 82ms/step - loss: 9.7260 - accuracy: 0.3145
8/8 [==============================] - 1s 106ms/step - loss: 9.7260 - accuracy: 0.3145 - val_loss: 8.3985 - val_accuracy: 0.2220
Epoch 13/100
1/8 [==>...........................] - ETA: 0s - loss: 8.7943 - accuracy: 0.1980
2/8 [======>.......................] - ETA: 0s - loss: 8.5508 - accuracy: 0.2680
3/8 [==========>...................] - ETA: 0s - loss: 8.0974 - accuracy: 0.2900
4/8 [==============>...............] - ETA: 0s - loss: 7.8664 - accuracy: 0.2255
5/8 [=================>............] - ETA: 0s - loss: 7.7025 - accuracy: 0.2266
6/8 [=====================>........] - ETA: 0s - loss: 7.4502 - accuracy: 0.2493
7/8 [=========================>....] - ETA: 0s - loss: 7.2701 - accuracy: 0.2656
8/8 [==============================] - 1s 84ms/step - loss: 7.1541 - accuracy: 0.2762
8/8 [==============================] - 1s 109ms/step - loss: 7.1541 - accuracy: 0.2762 - val_loss: 6.5115 - val_accuracy: 0.0060
Epoch 14/100
1/8 [==>...........................] - ETA: 0s - loss: 7.4132 - accuracy: 0.0090
2/8 [======>.......................] - ETA: 0s - loss: 6.9514 - accuracy: 0.1175
3/8 [==========>...................] - ETA: 0s - loss: 6.5947 - accuracy: 0.1867
4/8 [==============>...............] - ETA: 0s - loss: 6.4060 - accuracy: 0.2272
5/8 [=================>............] - ETA: 0s - loss: 6.2763 - accuracy: 0.1868
6/8 [=====================>........] - ETA: 0s - loss: 6.0918 - accuracy: 0.1913
7/8 [=========================>....] - ETA: 0s - loss: 6.0256 - accuracy: 0.2171
8/8 [==============================] - 1s 83ms/step - loss: 6.0020 - accuracy: 0.2333
8/8 [==============================] - 1s 107ms/step - loss: 6.0020 - accuracy: 0.2333 - val_loss: 5.7089 - val_accuracy: 0.3540
Epoch 15/100
1/8 [==>...........................] - ETA: 0s - loss: 6.3974 - accuracy: 0.3650
2/8 [======>.......................] - ETA: 0s - loss: 6.1777 - accuracy: 0.1860
3/8 [==========>...................] - ETA: 0s - loss: 6.1533 - accuracy: 0.2340
4/8 [==============>...............] - ETA: 0s - loss: 5.9956 - accuracy: 0.2680
5/8 [=================>............] - ETA: 0s - loss: 6.0698 - accuracy: 0.2814
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8/8 [==============================] - 1s 80ms/step - loss: 5.8480 - accuracy: 0.3079
8/8 [==============================] - 1s 103ms/step - loss: 5.8480 - accuracy: 0.3079 - val_loss: 5.1956 - val_accuracy: 0.3540
Epoch 16/100
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2/8 [======>.......................] - ETA: 0s - loss: 5.4142 - accuracy: 0.2805
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8/8 [==============================] - 1s 81ms/step - loss: 5.2198 - accuracy: 0.3135
8/8 [==============================] - 1s 105ms/step - loss: 5.2198 - accuracy: 0.3135 - val_loss: 4.3036 - val_accuracy: 0.3540
Epoch 17/100
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2/8 [======>.......................] - ETA: 0s - loss: 4.5159 - accuracy: 0.3495
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8/8 [==============================] - 1s 85ms/step - loss: 4.2853 - accuracy: 0.3358
8/8 [==============================] - 1s 108ms/step - loss: 4.2853 - accuracy: 0.3358 - val_loss: 3.5036 - val_accuracy: 0.3540
Epoch 18/100
1/8 [==>...........................] - ETA: 0s - loss: 3.3268 - accuracy: 0.3400
2/8 [======>.......................] - ETA: 0s - loss: 3.7829 - accuracy: 0.2825
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4/8 [==============>...............] - ETA: 0s - loss: 3.6596 - accuracy: 0.3295
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6/8 [=====================>........] - ETA: 0s - loss: 3.5377 - accuracy: 0.3160
7/8 [=========================>....] - ETA: 0s - loss: 3.4896 - accuracy: 0.3170
8/8 [==============================] - 1s 80ms/step - loss: 3.4849 - accuracy: 0.3211
8/8 [==============================] - 1s 104ms/step - loss: 3.4849 - accuracy: 0.3211 - val_loss: 3.0439 - val_accuracy: 0.3540
Epoch 19/100
1/8 [==>...........................] - ETA: 0s - loss: 2.9193 - accuracy: 0.3790
2/8 [======>.......................] - ETA: 0s - loss: 3.0879 - accuracy: 0.3585
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4/8 [==============>...............] - ETA: 0s - loss: 3.0735 - accuracy: 0.3507
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6/8 [=====================>........] - ETA: 0s - loss: 3.0296 - accuracy: 0.3282
7/8 [=========================>....] - ETA: 0s - loss: 3.0182 - accuracy: 0.3294
8/8 [==============================] - 1s 81ms/step - loss: 3.0576 - accuracy: 0.3309
8/8 [==============================] - 1s 105ms/step - loss: 3.0576 - accuracy: 0.3309 - val_loss: 2.8149 - val_accuracy: 0.3540
Epoch 20/100
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2/8 [======>.......................] - ETA: 0s - loss: 3.0050 - accuracy: 0.3545
3/8 [==========>...................] - ETA: 0s - loss: 2.9530 - accuracy: 0.3580
4/8 [==============>...............] - ETA: 0s - loss: 2.8695 - accuracy: 0.3548
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7/8 [=========================>....] - ETA: 0s - loss: 2.9697 - accuracy: 0.3504
8/8 [==============================] - 1s 83ms/step - loss: 2.9844 - accuracy: 0.3514
8/8 [==============================] - 1s 106ms/step - loss: 2.9844 - accuracy: 0.3514 - val_loss: 2.9165 - val_accuracy: 0.3540
Epoch 21/100
1/8 [==>...........................] - ETA: 0s - loss: 3.1442 - accuracy: 0.3590
2/8 [======>.......................] - ETA: 0s - loss: 3.0349 - accuracy: 0.3560
3/8 [==========>...................] - ETA: 0s - loss: 2.9712 - accuracy: 0.3630
4/8 [==============>...............] - ETA: 0s - loss: 2.9466 - accuracy: 0.3632
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7/8 [=========================>....] - ETA: 0s - loss: 2.9627 - accuracy: 0.3541
8/8 [==============================] - 1s 78ms/step - loss: 2.9647 - accuracy: 0.3514
8/8 [==============================] - 1s 100ms/step - loss: 2.9647 - accuracy: 0.3514 - val_loss: 2.7729 - val_accuracy: 0.2220
Epoch 22/100
1/8 [==>...........................] - ETA: 0s - loss: 3.0732 - accuracy: 0.1960
2/8 [======>.......................] - ETA: 0s - loss: 2.9658 - accuracy: 0.2795
3/8 [==========>...................] - ETA: 0s - loss: 2.8690 - accuracy: 0.3050
4/8 [==============>...............] - ETA: 0s - loss: 2.8728 - accuracy: 0.3187
5/8 [=================>............] - ETA: 0s - loss: 2.8301 - accuracy: 0.3254
6/8 [=====================>........] - ETA: 0s - loss: 2.8094 - accuracy: 0.3292
7/8 [=========================>....] - ETA: 0s - loss: 2.8098 - accuracy: 0.3300
8/8 [==============================] - 1s 79ms/step - loss: 2.8082 - accuracy: 0.3295
8/8 [==============================] - 1s 103ms/step - loss: 2.8082 - accuracy: 0.3295 - val_loss: 2.6023 - val_accuracy: 0.3540
Epoch 23/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6233 - accuracy: 0.3540
2/8 [======>.......................] - ETA: 0s - loss: 2.7182 - accuracy: 0.3440
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4/8 [==============>...............] - ETA: 0s - loss: 2.6427 - accuracy: 0.3555
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8/8 [==============================] - 1s 78ms/step - loss: 2.6729 - accuracy: 0.3514
8/8 [==============================] - 1s 102ms/step - loss: 2.6729 - accuracy: 0.3514 - val_loss: 2.6725 - val_accuracy: 0.3540
Epoch 24/100
1/8 [==>...........................] - ETA: 0s - loss: 2.8146 - accuracy: 0.3420
2/8 [======>.......................] - ETA: 0s - loss: 2.7493 - accuracy: 0.3555
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4/8 [==============>...............] - ETA: 0s - loss: 2.7901 - accuracy: 0.3543
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6/8 [=====================>........] - ETA: 0s - loss: 2.7676 - accuracy: 0.3537
7/8 [=========================>....] - ETA: 0s - loss: 2.7702 - accuracy: 0.3507
8/8 [==============================] - 1s 76ms/step - loss: 2.7597 - accuracy: 0.3334
8/8 [==============================] - 1s 98ms/step - loss: 2.7597 - accuracy: 0.3334 - val_loss: 2.7188 - val_accuracy: 0.3540
Epoch 25/100
1/8 [==>...........................] - ETA: 0s - loss: 2.7465 - accuracy: 0.3510
2/8 [======>.......................] - ETA: 0s - loss: 2.6837 - accuracy: 0.3540
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5/8 [=================>............] - ETA: 0s - loss: 2.7094 - accuracy: 0.3304
6/8 [=====================>........] - ETA: 0s - loss: 2.6949 - accuracy: 0.3342
7/8 [=========================>....] - ETA: 0s - loss: 2.7041 - accuracy: 0.3189
8/8 [==============================] - 1s 73ms/step - loss: 2.7194 - accuracy: 0.3236
8/8 [==============================] - 1s 96ms/step - loss: 2.7194 - accuracy: 0.3236 - val_loss: 2.6190 - val_accuracy: 0.3540
Epoch 26/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6718 - accuracy: 0.3560
2/8 [======>.......................] - ETA: 0s - loss: 2.6411 - accuracy: 0.3460
3/8 [==========>...................] - ETA: 0s - loss: 2.6387 - accuracy: 0.2967
4/8 [==============>...............] - ETA: 0s - loss: 2.6569 - accuracy: 0.3142
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6/8 [=====================>........] - ETA: 0s - loss: 2.6399 - accuracy: 0.3053
7/8 [=========================>....] - ETA: 0s - loss: 2.6070 - accuracy: 0.2943
8/8 [==============================] - 1s 75ms/step - loss: 2.6111 - accuracy: 0.3009
8/8 [==============================] - 1s 98ms/step - loss: 2.6111 - accuracy: 0.3009 - val_loss: 2.6126 - val_accuracy: 0.3540
Epoch 27/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6602 - accuracy: 0.3350
2/8 [======>.......................] - ETA: 0s - loss: 2.6180 - accuracy: 0.2705
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6/8 [=====================>........] - ETA: 0s - loss: 2.6134 - accuracy: 0.2995
7/8 [=========================>....] - ETA: 0s - loss: 2.6247 - accuracy: 0.3084
8/8 [==============================] - 1s 76ms/step - loss: 2.6202 - accuracy: 0.3131
8/8 [==============================] - 1s 100ms/step - loss: 2.6202 - accuracy: 0.3131 - val_loss: 2.5998 - val_accuracy: 0.2220
Epoch 28/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5815 - accuracy: 0.2140
2/8 [======>.......................] - ETA: 0s - loss: 2.7193 - accuracy: 0.2630
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4/8 [==============>...............] - ETA: 0s - loss: 2.6813 - accuracy: 0.2685
5/8 [=================>............] - ETA: 0s - loss: 2.6672 - accuracy: 0.2856
6/8 [=====================>........] - ETA: 0s - loss: 2.6440 - accuracy: 0.2988
7/8 [=========================>....] - ETA: 0s - loss: 2.6374 - accuracy: 0.2889
8/8 [==============================] - 1s 72ms/step - loss: 2.6257 - accuracy: 0.3002
8/8 [==============================] - 1s 94ms/step - loss: 2.6257 - accuracy: 0.3002 - val_loss: 2.5841 - val_accuracy: 0.3540
Epoch 29/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5690 - accuracy: 0.3500
2/8 [======>.......................] - ETA: 0s - loss: 2.6096 - accuracy: 0.2775
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4/8 [==============>...............] - ETA: 0s - loss: 2.6310 - accuracy: 0.2715
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6/8 [=====================>........] - ETA: 0s - loss: 2.6213 - accuracy: 0.2768
7/8 [=========================>....] - ETA: 0s - loss: 2.5940 - accuracy: 0.2881
8/8 [==============================] - 1s 72ms/step - loss: 2.5928 - accuracy: 0.2937
8/8 [==============================] - 1s 95ms/step - loss: 2.5928 - accuracy: 0.2937 - val_loss: 2.7792 - val_accuracy: 0.2220
Epoch 30/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6354 - accuracy: 0.2140
2/8 [======>.......................] - ETA: 0s - loss: 2.6371 - accuracy: 0.2820
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4/8 [==============>...............] - ETA: 0s - loss: 2.5760 - accuracy: 0.3232
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6/8 [=====================>........] - ETA: 0s - loss: 2.6102 - accuracy: 0.3137
7/8 [=========================>....] - ETA: 0s - loss: 2.6197 - accuracy: 0.3153
8/8 [==============================] - 1s 70ms/step - loss: 2.6437 - accuracy: 0.3023
8/8 [==============================] - 1s 92ms/step - loss: 2.6437 - accuracy: 0.3023 - val_loss: 2.7079 - val_accuracy: 0.3540
Epoch 31/100
1/8 [==>...........................] - ETA: 0s - loss: 2.4265 - accuracy: 0.3670
2/8 [======>.......................] - ETA: 0s - loss: 2.6311 - accuracy: 0.3570
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6/8 [=====================>........] - ETA: 0s - loss: 2.6199 - accuracy: 0.2802
7/8 [=========================>....] - ETA: 0s - loss: 2.6099 - accuracy: 0.2890
8/8 [==============================] - 1s 74ms/step - loss: 2.6340 - accuracy: 0.2952
8/8 [==============================] - 1s 97ms/step - loss: 2.6340 - accuracy: 0.2952 - val_loss: 2.7205 - val_accuracy: 0.3540
Epoch 32/100
1/8 [==>...........................] - ETA: 0s - loss: 2.8946 - accuracy: 0.3550
2/8 [======>.......................] - ETA: 0s - loss: 2.6470 - accuracy: 0.3605
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7/8 [=========================>....] - ETA: 0s - loss: 2.5588 - accuracy: 0.3566
8/8 [==============================] - 1s 74ms/step - loss: 2.5724 - accuracy: 0.3396
8/8 [==============================] - 1s 96ms/step - loss: 2.5724 - accuracy: 0.3396 - val_loss: 2.6244 - val_accuracy: 0.3540
Epoch 33/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5941 - accuracy: 0.3500
2/8 [======>.......................] - ETA: 0s - loss: 2.5709 - accuracy: 0.3410
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4/8 [==============>...............] - ETA: 0s - loss: 2.5289 - accuracy: 0.3183
5/8 [=================>............] - ETA: 0s - loss: 2.5483 - accuracy: 0.3270
6/8 [=====================>........] - ETA: 0s - loss: 2.5350 - accuracy: 0.3078
7/8 [=========================>....] - ETA: 0s - loss: 2.5319 - accuracy: 0.3144
8/8 [==============================] - 1s 73ms/step - loss: 2.5448 - accuracy: 0.3153
8/8 [==============================] - 1s 97ms/step - loss: 2.5448 - accuracy: 0.3153 - val_loss: 2.5615 - val_accuracy: 0.2220
Epoch 34/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5661 - accuracy: 0.2190
2/8 [======>.......................] - ETA: 0s - loss: 2.5323 - accuracy: 0.2870
3/8 [==========>...................] - ETA: 0s - loss: 2.5251 - accuracy: 0.3137
4/8 [==============>...............] - ETA: 0s - loss: 2.5131 - accuracy: 0.3215
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6/8 [=====================>........] - ETA: 0s - loss: 2.5294 - accuracy: 0.3080
7/8 [=========================>....] - ETA: 0s - loss: 2.5258 - accuracy: 0.3136
8/8 [==============================] - 1s 75ms/step - loss: 2.5393 - accuracy: 0.3003
8/8 [==============================] - 1s 99ms/step - loss: 2.5393 - accuracy: 0.3003 - val_loss: 2.5958 - val_accuracy: 0.3540
Epoch 35/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5831 - accuracy: 0.3390
2/8 [======>.......................] - ETA: 0s - loss: 2.6506 - accuracy: 0.3445
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4/8 [==============>...............] - ETA: 0s - loss: 2.5453 - accuracy: 0.3167
5/8 [=================>............] - ETA: 0s - loss: 2.5557 - accuracy: 0.3228
6/8 [=====================>........] - ETA: 0s - loss: 2.6002 - accuracy: 0.3020
7/8 [=========================>....] - ETA: 0s - loss: 2.5907 - accuracy: 0.3106
8/8 [==============================] - 1s 78ms/step - loss: 2.5820 - accuracy: 0.3145
8/8 [==============================] - 1s 101ms/step - loss: 2.5820 - accuracy: 0.3145 - val_loss: 2.8399 - val_accuracy: 0.2220
Epoch 36/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6778 - accuracy: 0.2250
2/8 [======>.......................] - ETA: 0s - loss: 2.8003 - accuracy: 0.2795
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6/8 [=====================>........] - ETA: 0s - loss: 2.6884 - accuracy: 0.3050
7/8 [=========================>....] - ETA: 0s - loss: 2.6912 - accuracy: 0.2927
8/8 [==============================] - 1s 77ms/step - loss: 2.6748 - accuracy: 0.3026
8/8 [==============================] - 1s 99ms/step - loss: 2.6748 - accuracy: 0.3026 - val_loss: 2.9383 - val_accuracy: 0.3540
Epoch 37/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6760 - accuracy: 0.3560
2/8 [======>.......................] - ETA: 0s - loss: 2.7150 - accuracy: 0.2860
3/8 [==========>...................] - ETA: 0s - loss: 2.6512 - accuracy: 0.3030
4/8 [==============>...............] - ETA: 0s - loss: 2.6213 - accuracy: 0.3130
5/8 [=================>............] - ETA: 0s - loss: 2.6482 - accuracy: 0.3230
6/8 [=====================>........] - ETA: 0s - loss: 2.6815 - accuracy: 0.3277
7/8 [=========================>....] - ETA: 0s - loss: 2.6510 - accuracy: 0.3311
8/8 [==============================] - 1s 75ms/step - loss: 2.6865 - accuracy: 0.3338
8/8 [==============================] - 1s 99ms/step - loss: 2.6865 - accuracy: 0.3338 - val_loss: 2.8895 - val_accuracy: 0.3540
Epoch 38/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5429 - accuracy: 0.3600
2/8 [======>.......................] - ETA: 0s - loss: 2.7150 - accuracy: 0.3390
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4/8 [==============>...............] - ETA: 0s - loss: 2.7036 - accuracy: 0.3147
5/8 [=================>............] - ETA: 0s - loss: 2.7450 - accuracy: 0.3212
6/8 [=====================>........] - ETA: 0s - loss: 2.7317 - accuracy: 0.2995
7/8 [=========================>....] - ETA: 0s - loss: 2.7001 - accuracy: 0.3066
8/8 [==============================] - 1s 82ms/step - loss: 2.6968 - accuracy: 0.3103
8/8 [==============================] - 1s 105ms/step - loss: 2.6968 - accuracy: 0.3103 - val_loss: 2.8777 - val_accuracy: 0.2220
Epoch 39/100
1/8 [==>...........................] - ETA: 0s - loss: 2.7722 - accuracy: 0.2140
2/8 [======>.......................] - ETA: 0s - loss: 2.7152 - accuracy: 0.2895
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7/8 [=========================>....] - ETA: 0s - loss: 2.6420 - accuracy: 0.2903
8/8 [==============================] - 1s 77ms/step - loss: 2.6484 - accuracy: 0.2959
8/8 [==============================] - 1s 100ms/step - loss: 2.6484 - accuracy: 0.2959 - val_loss: 2.6170 - val_accuracy: 0.3540
Epoch 40/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6552 - accuracy: 0.3730
2/8 [======>.......................] - ETA: 0s - loss: 2.5508 - accuracy: 0.3645
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4/8 [==============>...............] - ETA: 0s - loss: 2.5000 - accuracy: 0.3618
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7/8 [=========================>....] - ETA: 0s - loss: 2.5494 - accuracy: 0.3367
8/8 [==============================] - 1s 76ms/step - loss: 2.5516 - accuracy: 0.3385
8/8 [==============================] - 1s 98ms/step - loss: 2.5516 - accuracy: 0.3385 - val_loss: 2.6001 - val_accuracy: 0.2220
Epoch 41/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6047 - accuracy: 0.2130
2/8 [======>.......................] - ETA: 0s - loss: 2.5202 - accuracy: 0.2780
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8/8 [==============================] - 1s 77ms/step - loss: 2.5067 - accuracy: 0.3339
8/8 [==============================] - 1s 100ms/step - loss: 2.5067 - accuracy: 0.3339 - val_loss: 2.5680 - val_accuracy: 0.3540
Epoch 42/100
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8/8 [==============================] - 1s 83ms/step - loss: 2.5990 - accuracy: 0.3123
8/8 [==============================] - 1s 105ms/step - loss: 2.5990 - accuracy: 0.3123 - val_loss: 2.6784 - val_accuracy: 0.3540
Epoch 43/100
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2/8 [======>.......................] - ETA: 0s - loss: 2.6157 - accuracy: 0.2770
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7/8 [=========================>....] - ETA: 0s - loss: 2.5699 - accuracy: 0.3064
8/8 [==============================] - 1s 76ms/step - loss: 2.5663 - accuracy: 0.3130
8/8 [==============================] - 1s 100ms/step - loss: 2.5663 - accuracy: 0.3130 - val_loss: 2.5836 - val_accuracy: 0.2220
Epoch 44/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5986 - accuracy: 0.2250
2/8 [======>.......................] - ETA: 0s - loss: 2.6346 - accuracy: 0.2855
3/8 [==========>...................] - ETA: 0s - loss: 2.5846 - accuracy: 0.3150
4/8 [==============>...............] - ETA: 0s - loss: 2.5710 - accuracy: 0.3243
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7/8 [=========================>....] - ETA: 0s - loss: 2.5479 - accuracy: 0.3170
8/8 [==============================] - 1s 77ms/step - loss: 2.5503 - accuracy: 0.3207
8/8 [==============================] - 1s 100ms/step - loss: 2.5503 - accuracy: 0.3207 - val_loss: 2.4908 - val_accuracy: 0.3540
Epoch 45/100
1/8 [==>...........................] - ETA: 0s - loss: 2.4739 - accuracy: 0.3340
2/8 [======>.......................] - ETA: 0s - loss: 2.5764 - accuracy: 0.3405
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4/8 [==============>...............] - ETA: 0s - loss: 2.5842 - accuracy: 0.3475
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7/8 [=========================>....] - ETA: 0s - loss: 2.5594 - accuracy: 0.3331
8/8 [==============================] - 1s 80ms/step - loss: 2.5589 - accuracy: 0.3195
8/8 [==============================] - 1s 103ms/step - loss: 2.5589 - accuracy: 0.3195 - val_loss: 2.5246 - val_accuracy: 0.3540
Epoch 46/100
1/8 [==>...........................] - ETA: 0s - loss: 2.6316 - accuracy: 0.3250
2/8 [======>.......................] - ETA: 0s - loss: 2.5853 - accuracy: 0.3295
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4/8 [==============>...............] - ETA: 0s - loss: 2.5742 - accuracy: 0.3465
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6/8 [=====================>........] - ETA: 0s - loss: 2.5652 - accuracy: 0.3283
7/8 [=========================>....] - ETA: 0s - loss: 2.5667 - accuracy: 0.3327
8/8 [==============================] - 1s 81ms/step - loss: 2.5622 - accuracy: 0.3384
8/8 [==============================] - 1s 104ms/step - loss: 2.5622 - accuracy: 0.3384 - val_loss: 2.4523 - val_accuracy: 0.3540
Epoch 47/100
1/8 [==>...........................] - ETA: 0s - loss: 2.4082 - accuracy: 0.3600
2/8 [======>.......................] - ETA: 0s - loss: 2.5653 - accuracy: 0.3430
3/8 [==========>...................] - ETA: 0s - loss: 2.5873 - accuracy: 0.2977
4/8 [==============>...............] - ETA: 0s - loss: 2.5638 - accuracy: 0.3192
5/8 [=================>............] - ETA: 0s - loss: 2.5745 - accuracy: 0.3258
6/8 [=====================>........] - ETA: 0s - loss: 2.5850 - accuracy: 0.3070
7/8 [=========================>....] - ETA: 0s - loss: 2.6154 - accuracy: 0.3069
8/8 [==============================] - 1s 77ms/step - loss: 2.6154 - accuracy: 0.3143
8/8 [==============================] - 1s 100ms/step - loss: 2.6154 - accuracy: 0.3143 - val_loss: 2.5165 - val_accuracy: 0.2220
Epoch 48/100
1/8 [==>...........................] - ETA: 0s - loss: 2.5770 - accuracy: 0.2050
2/8 [======>.......................] - ETA: 0s - loss: 2.6947 - accuracy: 0.2590
3/8 [==========>...................] - ETA: 0s - loss: 2.7268 - accuracy: 0.2493
4/8 [==============>...............] - ETA: 0s - loss: 2.7088 - accuracy: 0.2027
5/8 [=================>............] - ETA: 0s - loss: 2.7961 - accuracy: 0.2332
6/8 [=====================>........] - ETA: 0s - loss: 2.8122 - accuracy: 0.2305
7/8 [=========================>....] - ETA: 0s - loss: 2.8005 - accuracy: 0.2290
8/8 [==============================] - 1s 76ms/step - loss: 2.8042 - accuracy: 0.2448
8/8 [==============================] - 1s 98ms/step - loss: 2.8042 - accuracy: 0.2448 - val_loss: 3.0307 - val_accuracy: 0.0590
Epoch 49/100
1/8 [==>...........................] - ETA: 0s - loss: 3.1233 - accuracy: 0.0630
2/8 [======>.......................] - ETA: 0s - loss: 2.9578 - accuracy: 0.1490
3/8 [==========>...................] - ETA: 0s - loss: 3.1025 - accuracy: 0.2167
4/8 [==============>...............] - ETA: 0s - loss: 3.2608 - accuracy: 0.1735
5/8 [=================>............] - ETA: 0s - loss: 3.3132 - accuracy: 0.1760
6/8 [=====================>........] - ETA: 0s - loss: 3.4275 - accuracy: 0.2040
7/8 [=========================>....] - ETA: 0s - loss: 3.4684 - accuracy: 0.1833
8/8 [==============================] - 1s 79ms/step - loss: 3.4157 - accuracy: 0.1888
8/8 [==============================] - 1s 101ms/step - loss: 3.4157 - accuracy: 0.1888 - val_loss: 3.2738 - val_accuracy: 0.3540
Epoch 50/100
1/8 [==>...........................] - ETA: 0s - loss: 3.4537 - accuracy: 0.3550
2/8 [======>.......................] - ETA: 0s - loss: 3.4749 - accuracy: 0.3525
3/8 [==========>...................] - ETA: 0s - loss: 3.6756 - accuracy: 0.3020
4/8 [==============>...............] - ETA: 0s - loss: 3.6634 - accuracy: 0.3117
5/8 [=================>............] - ETA: 0s - loss: 3.6448 - accuracy: 0.2552
6/8 [=====================>........] - ETA: 0s - loss: 3.6158 - accuracy: 0.2445
7/8 [=========================>....] - ETA: 0s - loss: 3.5775 - accuracy: 0.2613
8/8 [==============================] - 1s 74ms/step - loss: 3.5886 - accuracy: 0.2342
8/8 [==============================] - 1s 97ms/step - loss: 3.5886 - accuracy: 0.2342 - val_loss: 3.7406 - val_accuracy: 0.2220
Epoch 51/100
1/8 [==>...........................] - ETA: 0s - loss: 3.9930 - accuracy: 0.2020
2/8 [======>.......................] - ETA: 0s - loss: 3.9656 - accuracy: 0.2765
3/8 [==========>...................] - ETA: 0s - loss: 4.2737 - accuracy: 0.1963
4/8 [==============>...............] - ETA: 0s - loss: 4.5042 - accuracy: 0.2017
5/8 [=================>............] - ETA: 0s - loss: 4.8951 - accuracy: 0.2312
6/8 [=====================>........] - ETA: 0s - loss: 5.1568 - accuracy: 0.1978
7/8 [=========================>....] - ETA: 0s - loss: 5.2795 - accuracy: 0.1783
8/8 [==============================] - 1s 74ms/step - loss: 5.3789 - accuracy: 0.1832
8/8 [==============================] - 1s 96ms/step - loss: 5.3789 - accuracy: 0.1832 - val_loss: 7.2811 - val_accuracy: 0.3540
Epoch 52/100
1/8 [==>...........................] - ETA: 0s - loss: 7.8096 - accuracy: 0.3480
2/8 [======>.......................] - ETA: 0s - loss: 7.7726 - accuracy: 0.3445
3/8 [==========>...................] - ETA: 0s - loss: 7.7585 - accuracy: 0.3023
4/8 [==============>...............] - ETA: 0s - loss: 7.8871 - accuracy: 0.2370
5/8 [=================>............] - ETA: 0s - loss: 7.7741 - accuracy: 0.2610
6/8 [=====================>........] - ETA: 0s - loss: 7.6489 - accuracy: 0.2187
7/8 [=========================>....] - ETA: 0s - loss: 7.5755 - accuracy: 0.2204
8/8 [==============================] - 1s 72ms/step - loss: 7.5505 - accuracy: 0.2363
8/8 [==============================] - 1s 94ms/step - loss: 7.5505 - accuracy: 0.2363 - val_loss: 6.9604 - val_accuracy: 0.3540
Epoch 53/100
1/8 [==>...........................] - ETA: 0s - loss: 7.5103 - accuracy: 0.3310
2/8 [======>.......................] - ETA: 0s - loss: 7.7278 - accuracy: 0.1780
3/8 [==========>...................] - ETA: 0s - loss: 7.4974 - accuracy: 0.1907
4/8 [==============>...............] - ETA: 0s - loss: 7.7865 - accuracy: 0.2313
5/8 [=================>............] - ETA: 0s - loss: 8.1950 - accuracy: 0.1944
6/8 [=====================>........] - ETA: 0s - loss: 8.4522 - accuracy: 0.2192
7/8 [=========================>....] - ETA: 0s - loss: 8.7306 - accuracy: 0.2180
8/8 [==============================] - 1s 84ms/step - loss: 8.9654 - accuracy: 0.2359
8/8 [==============================] - 1s 108ms/step - loss: 8.9654 - accuracy: 0.2359 - val_loss: 10.8050 - val_accuracy: 0.3540
Epoch 54/100
1/8 [==>...........................] - ETA: 0s - loss: 13.1392 - accuracy: 0.3280
2/8 [======>.......................] - ETA: 0s - loss: 12.3559 - accuracy: 0.1835
3/8 [==========>...................] - ETA: 0s - loss: 11.5390 - accuracy: 0.1940
4/8 [==============>...............] - ETA: 0s - loss: 11.6075 - accuracy: 0.2225
5/8 [=================>............] - ETA: 0s - loss: 11.4646 - accuracy: 0.2186
6/8 [=====================>........] - ETA: 0s - loss: 11.3974 - accuracy: 0.1823
7/8 [=========================>....] - ETA: 0s - loss: 11.1077 - accuracy: 0.2103
8/8 [==============================] - 1s 75ms/step - loss: 10.9562 - accuracy: 0.1932
8/8 [==============================] - 1s 97ms/step - loss: 10.9562 - accuracy: 0.1932 - val_loss: 10.3756 - val_accuracy: 0.0470
Epoch 55/100
1/8 [==>...........................] - ETA: 0s - loss: 11.9632 - accuracy: 0.0610
2/8 [======>.......................] - ETA: 0s - loss: 11.0972 - accuracy: 0.1300
3/8 [==========>...................] - ETA: 0s - loss: 11.2198 - accuracy: 0.2090
4/8 [==============>...............] - ETA: 0s - loss: 11.1596 - accuracy: 0.1587
5/8 [=================>............] - ETA: 0s - loss: 11.0785 - accuracy: 0.1734
6/8 [=====================>........] - ETA: 0s - loss: 11.0438 - accuracy: 0.2053
7/8 [=========================>....] - ETA: 0s - loss: 10.9535 - accuracy: 0.1770
8/8 [==============================] - 1s 72ms/step - loss: 10.8967 - accuracy: 0.1610
8/8 [==============================] - 1s 94ms/step - loss: 10.8967 - accuracy: 0.1610 - val_loss: 12.1359 - val_accuracy: 0.0460
Epoch 56/100
1/8 [==>...........................] - ETA: 0s - loss: 12.5580 - accuracy: 0.0540
2/8 [======>.......................] - ETA: 0s - loss: 12.0712 - accuracy: 0.2095
3/8 [==========>...................] - ETA: 0s - loss: 12.3315 - accuracy: 0.2130
4/8 [==============>...............] - ETA: 0s - loss: 12.2229 - accuracy: 0.1660
5/8 [=================>............] - ETA: 0s - loss: 12.7657 - accuracy: 0.2024
6/8 [=====================>........] - ETA: 0s - loss: 13.3161 - accuracy: 0.1810
7/8 [=========================>....] - ETA: 0s - loss: 13.6125 - accuracy: 0.2024
8/8 [==============================] - 1s 73ms/step - loss: 13.8850 - accuracy: 0.2048
8/8 [==============================] - 1s 95ms/step - loss: 13.8850 - accuracy: 0.2048 - val_loss: 17.3227 - val_accuracy: 0.0470
Epoch 57/100
1/8 [==>...........................] - ETA: 0s - loss: 17.9582 - accuracy: 0.0500
2/8 [======>.......................] - ETA: 0s - loss: 18.5836 - accuracy: 0.1875
3/8 [==========>...................] - ETA: 0s - loss: 18.5963 - accuracy: 0.2453
4/8 [==============>...............] - ETA: 0s - loss: 18.2433 - accuracy: 0.1842
5/8 [=================>............] - ETA: 0s - loss: 18.6456 - accuracy: 0.1868
6/8 [=====================>........] - ETA: 0s - loss: 17.8339 - accuracy: 0.2203
7/8 [=========================>....] - ETA: 0s - loss: 17.5069 - accuracy: 0.2427
8/8 [==============================] - 1s 79ms/step - loss: 17.1827 - accuracy: 0.2560
8/8 [==============================] - 1s 102ms/step - loss: 17.1827 - accuracy: 0.2560 - val_loss: 14.5769 - val_accuracy: 0.0030
Epoch 58/100
1/8 [==>...........................] - ETA: 0s - loss: 14.9930 - accuracy: 0.0030
2/8 [======>.......................] - ETA: 0s - loss: 15.5294 - accuracy: 0.0240
3/8 [==========>...................] - ETA: 0s - loss: 15.5513 - accuracy: 0.0903
4/8 [==============>...............] - ETA: 0s - loss: 16.0377 - accuracy: 0.1562
5/8 [=================>............] - ETA: 0s - loss: 16.1952 - accuracy: 0.1274
6/8 [=====================>........] - ETA: 0s - loss: 16.1324 - accuracy: 0.1633
7/8 [=========================>....] - ETA: 0s - loss: 16.0412 - accuracy: 0.1450
8/8 [==============================] - 1s 74ms/step - loss: 15.9320 - accuracy: 0.1553
8/8 [==============================] - 1s 97ms/step - loss: 15.9320 - accuracy: 0.1553 - val_loss: 14.0604 - val_accuracy: 0.0470
Epoch 59/100
1/8 [==>...........................] - ETA: 0s - loss: 13.5417 - accuracy: 0.0570
2/8 [======>.......................] - ETA: 0s - loss: 15.4031 - accuracy: 0.0600
3/8 [==========>...................] - ETA: 0s - loss: 15.8218 - accuracy: 0.1620
4/8 [==============>...............] - ETA: 0s - loss: 16.9018 - accuracy: 0.2083
5/8 [=================>............] - ETA: 0s - loss: 17.0367 - accuracy: 0.1732
6/8 [=====================>........] - ETA: 0s - loss: 17.3834 - accuracy: 0.1803
7/8 [=========================>....] - ETA: 0s - loss: 17.5656 - accuracy: 0.2056
8/8 [==============================] - 1s 75ms/step - loss: 17.4663 - accuracy: 0.2256
8/8 [==============================] - 1s 97ms/step - loss: 17.4663 - accuracy: 0.2256 - val_loss: 20.3876 - val_accuracy: 0.0470
Epoch 60/100
1/8 [==>...........................] - ETA: 0s - loss: 17.7802 - accuracy: 0.0490
2/8 [======>.......................] - ETA: 0s - loss: 17.9820 - accuracy: 0.1315
3/8 [==========>...................] - ETA: 0s - loss: 17.9897 - accuracy: 0.2087
4/8 [==============>...............] - ETA: 0s - loss: 17.5153 - accuracy: 0.1593
5/8 [=================>............] - ETA: 0s - loss: 17.2130 - accuracy: 0.1280
6/8 [=====================>........] - ETA: 0s - loss: 17.1167 - accuracy: 0.1163
7/8 [=========================>....] - ETA: 0s - loss: 17.1180 - accuracy: 0.1490
8/8 [==============================] - 1s 75ms/step - loss: 17.2643 - accuracy: 0.1323
8/8 [==============================] - 1s 97ms/step - loss: 17.2643 - accuracy: 0.1323 - val_loss: 18.1006 - val_accuracy: 0.2220
Epoch 61/100
1/8 [==>...........................] - ETA: 0s - loss: 17.2762 - accuracy: 0.2230
2/8 [======>.......................] - ETA: 0s - loss: 16.6167 - accuracy: 0.2925
3/8 [==========>...................] - ETA: 0s - loss: 17.8997 - accuracy: 0.2133
4/8 [==============>...............] - ETA: 0s - loss: 19.4854 - accuracy: 0.1730
5/8 [=================>............] - ETA: 0s - loss: 19.6441 - accuracy: 0.2056
6/8 [=====================>........] - ETA: 0s - loss: 19.6241 - accuracy: 0.1812
7/8 [=========================>....] - ETA: 0s - loss: 20.0085 - accuracy: 0.1890
8/8 [==============================] - 1s 82ms/step - loss: 20.1491 - accuracy: 0.2131
8/8 [==============================] - 1s 106ms/step - loss: 20.1491 - accuracy: 0.2131 - val_loss: 23.5334 - val_accuracy: 0.3540
Epoch 62/100
1/8 [==>...........................] - ETA: 0s - loss: 21.1106 - accuracy: 0.3710
2/8 [======>.......................] - ETA: 0s - loss: 21.3073 - accuracy: 0.3655
3/8 [==========>...................] - ETA: 0s - loss: 20.9974 - accuracy: 0.2467
4/8 [==============>...............] - ETA: 0s - loss: 20.9568 - accuracy: 0.2400
5/8 [=================>............] - ETA: 0s - loss: 21.0124 - accuracy: 0.1934
6/8 [=====================>........] - ETA: 0s - loss: 20.9246 - accuracy: 0.2163
7/8 [=========================>....] - ETA: 0s - loss: 21.1839 - accuracy: 0.1877
8/8 [==============================] - 1s 77ms/step - loss: 20.8603 - accuracy: 0.1735
8/8 [==============================] - 1s 100ms/step - loss: 20.8603 - accuracy: 0.1735 - val_loss: 20.6280 - val_accuracy: 0.2220
Epoch 63/100
1/8 [==>...........................] - ETA: 0s - loss: 20.0814 - accuracy: 0.1960
2/8 [======>.......................] - ETA: 0s - loss: 20.1526 - accuracy: 0.2830
3/8 [==========>...................] - ETA: 0s - loss: 21.3790 - accuracy: 0.2077
4/8 [==============>...............] - ETA: 0s - loss: 21.4187 - accuracy: 0.2432
5/8 [=================>............] - ETA: 0s - loss: 20.9179 - accuracy: 0.1968
6/8 [=====================>........] - ETA: 0s - loss: 21.1446 - accuracy: 0.2023
7/8 [=========================>....] - ETA: 0s - loss: 20.9283 - accuracy: 0.1746
8/8 [==============================] - 1s 74ms/step - loss: 21.0315 - accuracy: 0.1943
8/8 [==============================] - 1s 98ms/step - loss: 21.0315 - accuracy: 0.1943 - val_loss: 26.8127 - val_accuracy: 0.0250
Epoch 64/100
1/8 [==>...........................] - ETA: 0s - loss: 24.7651 - accuracy: 0.0380
2/8 [======>.......................] - ETA: 0s - loss: 22.4872 - accuracy: 0.0420
3/8 [==========>...................] - ETA: 0s - loss: 21.4396 - accuracy: 0.0413
4/8 [==============>...............] - ETA: 0s - loss: 22.5435 - accuracy: 0.0820
5/8 [=================>............] - ETA: 0s - loss: 23.0087 - accuracy: 0.1328
6/8 [=====================>........] - ETA: 0s - loss: 23.3648 - accuracy: 0.1213
7/8 [=========================>....] - ETA: 0s - loss: 23.5821 - accuracy: 0.1553
8/8 [==============================] - 1s 77ms/step - loss: 23.6189 - accuracy: 0.1616
8/8 [==============================] - 1s 100ms/step - loss: 23.6189 - accuracy: 0.1616 - val_loss: 25.5706 - val_accuracy: 0.3540
Epoch 65/100
1/8 [==>...........................] - ETA: 0s - loss: 24.6516 - accuracy: 0.3540
2/8 [======>.......................] - ETA: 0s - loss: 24.8944 - accuracy: 0.3540
3/8 [==========>...................] - ETA: 0s - loss: 24.6777 - accuracy: 0.2410
4/8 [==============>...............] - ETA: 0s - loss: 24.4075 - accuracy: 0.2682
5/8 [=================>............] - ETA: 0s - loss: 23.8567 - accuracy: 0.2606
6/8 [=====================>........] - ETA: 0s - loss: 23.6952 - accuracy: 0.2532
7/8 [=========================>....] - ETA: 0s - loss: 23.2968 - accuracy: 0.2176
8/8 [==============================] - 1s 79ms/step - loss: 23.1121 - accuracy: 0.1952
8/8 [==============================] - 1s 102ms/step - loss: 23.1121 - accuracy: 0.1952 - val_loss: 22.0581 - val_accuracy: 0.3540
Epoch 66/100
1/8 [==>...........................] - ETA: 0s - loss: 20.4917 - accuracy: 0.3570
2/8 [======>.......................] - ETA: 0s - loss: 20.7669 - accuracy: 0.2060
3/8 [==========>...................] - ETA: 0s - loss: 20.6629 - accuracy: 0.2110
4/8 [==============>...............] - ETA: 0s - loss: 21.2423 - accuracy: 0.1710
5/8 [=================>............] - ETA: 0s - loss: 21.5415 - accuracy: 0.2094
6/8 [=====================>........] - ETA: 0s - loss: 21.2153 - accuracy: 0.1833
7/8 [=========================>....] - ETA: 0s - loss: 21.1520 - accuracy: 0.2059
8/8 [==============================] - 1s 79ms/step - loss: 21.1504 - accuracy: 0.2093
8/8 [==============================] - 1s 102ms/step - loss: 21.1504 - accuracy: 0.2093 - val_loss: 21.3148 - val_accuracy: 0.2220
Epoch 67/100
1/8 [==>...........................] - ETA: 0s - loss: 19.5480 - accuracy: 0.2260
2/8 [======>.......................] - ETA: 0s - loss: 18.9214 - accuracy: 0.2870
3/8 [==========>...................] - ETA: 0s - loss: 19.1185 - accuracy: 0.2947
4/8 [==============>...............] - ETA: 0s - loss: 18.7131 - accuracy: 0.2215
5/8 [=================>............] - ETA: 0s - loss: 17.8311 - accuracy: 0.2230
6/8 [=====================>........] - ETA: 0s - loss: 17.1972 - accuracy: 0.1873
7/8 [=========================>....] - ETA: 0s - loss: 16.9024 - accuracy: 0.1679
8/8 [==============================] - 1s 76ms/step - loss: 16.6114 - accuracy: 0.1909
8/8 [==============================] - 1s 101ms/step - loss: 16.6114 - accuracy: 0.1909 - val_loss: 16.8153 - val_accuracy: 0.0250
Epoch 68/100
1/8 [==>...........................] - ETA: 0s - loss: 15.0669 - accuracy: 0.0290
2/8 [======>.......................] - ETA: 0s - loss: 15.7888 - accuracy: 0.1210
3/8 [==========>...................] - ETA: 0s - loss: 15.8624 - accuracy: 0.2013
4/8 [==============>...............] - ETA: 0s - loss: 15.7400 - accuracy: 0.2460
5/8 [=================>............] - ETA: 0s - loss: 16.3353 - accuracy: 0.2074
6/8 [=====================>........] - ETA: 0s - loss: 16.4753 - accuracy: 0.1852
7/8 [=========================>....] - ETA: 0s - loss: 16.8816 - accuracy: 0.2090
8/8 [==============================] - 1s 83ms/step - loss: 17.0970 - accuracy: 0.2265
8/8 [==============================] - 1s 107ms/step - loss: 17.0970 - accuracy: 0.2265 - val_loss: 20.4583 - val_accuracy: 0.3540
Epoch 69/100
1/8 [==>...........................] - ETA: 0s - loss: 18.8477 - accuracy: 0.3780
2/8 [======>.......................] - ETA: 0s - loss: 20.2231 - accuracy: 0.2020
3/8 [==========>...................] - ETA: 0s - loss: 19.5419 - accuracy: 0.2517
4/8 [==============>...............] - ETA: 0s - loss: 20.0624 - accuracy: 0.2772
5/8 [=================>............] - ETA: 0s - loss: 20.2858 - accuracy: 0.2674
6/8 [=====================>........] - ETA: 0s - loss: 20.2281 - accuracy: 0.2812
7/8 [=========================>....] - ETA: 0s - loss: 19.8513 - accuracy: 0.2914
8/8 [==============================] - 1s 75ms/step - loss: 19.7133 - accuracy: 0.2623
8/8 [==============================] - 1s 98ms/step - loss: 19.7133 - accuracy: 0.2623 - val_loss: 17.1636 - val_accuracy: 0.2220
Epoch 70/100
1/8 [==>...........................] - ETA: 0s - loss: 14.8119 - accuracy: 0.2090
2/8 [======>.......................] - ETA: 0s - loss: 15.5043 - accuracy: 0.1060
3/8 [==========>...................] - ETA: 0s - loss: 15.1500 - accuracy: 0.1900
4/8 [==============>...............] - ETA: 0s - loss: 15.4365 - accuracy: 0.1548
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7/8 [=========================>....] - ETA: 0s - loss: 16.2956 - accuracy: 0.1271
8/8 [==============================] - 1s 76ms/step - loss: 16.6904 - accuracy: 0.1527
8/8 [==============================] - 1s 98ms/step - loss: 16.6904 - accuracy: 0.1527 - val_loss: 19.0228 - val_accuracy: 0.0440
Epoch 71/100
1/8 [==>...........................] - ETA: 0s - loss: 16.6846 - accuracy: 0.0450
2/8 [======>.......................] - ETA: 0s - loss: 16.3789 - accuracy: 0.1440
3/8 [==========>...................] - ETA: 0s - loss: 17.7118 - accuracy: 0.1707
4/8 [==============>...............] - ETA: 0s - loss: 17.9659 - accuracy: 0.2148
5/8 [=================>............] - ETA: 0s - loss: 18.4653 - accuracy: 0.2440
6/8 [=====================>........] - ETA: 0s - loss: 18.7640 - accuracy: 0.2578
7/8 [=========================>....] - ETA: 0s - loss: 19.0885 - accuracy: 0.2491
8/8 [==============================] - 1s 74ms/step - loss: 19.1888 - accuracy: 0.2258
8/8 [==============================] - 1s 97ms/step - loss: 19.1888 - accuracy: 0.2258 - val_loss: 18.7329 - val_accuracy: 0.0470
Epoch 72/100
1/8 [==>...........................] - ETA: 0s - loss: 18.8419 - accuracy: 0.0420
2/8 [======>.......................] - ETA: 0s - loss: 19.1942 - accuracy: 0.1850
3/8 [==========>...................] - ETA: 0s - loss: 17.9930 - accuracy: 0.2420
4/8 [==============>...............] - ETA: 0s - loss: 17.8405 - accuracy: 0.2403
5/8 [=================>............] - ETA: 0s - loss: 18.0455 - accuracy: 0.1950
6/8 [=====================>........] - ETA: 0s - loss: 18.0103 - accuracy: 0.1637
7/8 [=========================>....] - ETA: 0s - loss: 17.8515 - accuracy: 0.1909
8/8 [==============================] - 1s 78ms/step - loss: 17.4029 - accuracy: 0.1914
8/8 [==============================] - 1s 101ms/step - loss: 17.4029 - accuracy: 0.1914 - val_loss: 15.3048 - val_accuracy: 0.2220
Epoch 73/100
1/8 [==>...........................] - ETA: 0s - loss: 14.8299 - accuracy: 0.2070
2/8 [======>.......................] - ETA: 0s - loss: 13.4701 - accuracy: 0.2760
3/8 [==========>...................] - ETA: 0s - loss: 14.2269 - accuracy: 0.1997
4/8 [==============>...............] - ETA: 0s - loss: 14.3058 - accuracy: 0.1610
5/8 [=================>............] - ETA: 0s - loss: 14.4248 - accuracy: 0.1996
6/8 [=====================>........] - ETA: 0s - loss: 14.9771 - accuracy: 0.2002
7/8 [=========================>....] - ETA: 0s - loss: 14.9844 - accuracy: 0.2214
8/8 [==============================] - 1s 75ms/step - loss: 15.4914 - accuracy: 0.1989
8/8 [==============================] - 1s 98ms/step - loss: 15.4914 - accuracy: 0.1989 - val_loss: 18.3546 - val_accuracy: 0.0140
Epoch 74/100
1/8 [==>...........................] - ETA: 0s - loss: 18.2378 - accuracy: 0.0140
2/8 [======>.......................] - ETA: 0s - loss: 18.3849 - accuracy: 0.1810
3/8 [==========>...................] - ETA: 0s - loss: 19.2301 - accuracy: 0.1917
4/8 [==============>...............] - ETA: 0s - loss: 19.1965 - accuracy: 0.2310
5/8 [=================>............] - ETA: 0s - loss: 18.8237 - accuracy: 0.2578
6/8 [=====================>........] - ETA: 0s - loss: 18.9147 - accuracy: 0.2157
7/8 [=========================>....] - ETA: 0s - loss: 18.6834 - accuracy: 0.1894
8/8 [==============================] - 1s 73ms/step - loss: 18.6283 - accuracy: 0.2070
8/8 [==============================] - 1s 95ms/step - loss: 18.6283 - accuracy: 0.2070 - val_loss: 17.8253 - val_accuracy: 0.2220
Epoch 75/100
1/8 [==>...........................] - ETA: 0s - loss: 19.0666 - accuracy: 0.2200
2/8 [======>.......................] - ETA: 0s - loss: 18.0681 - accuracy: 0.1195
3/8 [==========>...................] - ETA: 0s - loss: 18.3935 - accuracy: 0.0943
4/8 [==============>...............] - ETA: 0s - loss: 17.7896 - accuracy: 0.1580
5/8 [=================>............] - ETA: 0s - loss: 17.3327 - accuracy: 0.1718
6/8 [=====================>........] - ETA: 0s - loss: 17.2942 - accuracy: 0.2022
7/8 [=========================>....] - ETA: 0s - loss: 16.8591 - accuracy: 0.1821
8/8 [==============================] - 1s 76ms/step - loss: 16.3237 - accuracy: 0.2026
8/8 [==============================] - 1s 99ms/step - loss: 16.3237 - accuracy: 0.2026 - val_loss: 13.4431 - val_accuracy: 0.3540
Epoch 76/100
1/8 [==>...........................] - ETA: 0s - loss: 13.8697 - accuracy: 0.3480
2/8 [======>.......................] - ETA: 0s - loss: 13.0246 - accuracy: 0.2855
3/8 [==========>...................] - ETA: 0s - loss: 13.1007 - accuracy: 0.1937
4/8 [==============>...............] - ETA: 0s - loss: 12.9737 - accuracy: 0.2350
5/8 [=================>............] - ETA: 0s - loss: 13.3634 - accuracy: 0.1970
6/8 [=====================>........] - ETA: 0s - loss: 13.3887 - accuracy: 0.2217
7/8 [=========================>....] - ETA: 0s - loss: 13.3393 - accuracy: 0.2213
8/8 [==============================] - 1s 74ms/step - loss: 13.4697 - accuracy: 0.2363
8/8 [==============================] - 1s 96ms/step - loss: 13.4697 - accuracy: 0.2363 - val_loss: 13.4240 - val_accuracy: 0.3540
Epoch 77/100
1/8 [==>...........................] - ETA: 0s - loss: 14.5065 - accuracy: 0.3470
2/8 [======>.......................] - ETA: 0s - loss: 14.8187 - accuracy: 0.1910
3/8 [==========>...................] - ETA: 0s - loss: 14.3519 - accuracy: 0.2017
4/8 [==============>...............] - ETA: 0s - loss: 13.9940 - accuracy: 0.2412
5/8 [=================>............] - ETA: 0s - loss: 14.2021 - accuracy: 0.2632
6/8 [=====================>........] - ETA: 0s - loss: 14.1522 - accuracy: 0.2570
7/8 [=========================>....] - ETA: 0s - loss: 13.7515 - accuracy: 0.2519
8/8 [==============================] - 1s 73ms/step - loss: 13.8897 - accuracy: 0.2603
8/8 [==============================] - 1s 95ms/step - loss: 13.8897 - accuracy: 0.2603 - val_loss: 13.0405 - val_accuracy: 0.3540
Epoch 78/100
1/8 [==>...........................] - ETA: 0s - loss: 12.2727 - accuracy: 0.3460
2/8 [======>.......................] - ETA: 0s - loss: 14.0518 - accuracy: 0.1775
3/8 [==========>...................] - ETA: 0s - loss: 13.9833 - accuracy: 0.1870
4/8 [==============>...............] - ETA: 0s - loss: 13.8496 - accuracy: 0.2265
5/8 [=================>............] - ETA: 0s - loss: 13.4358 - accuracy: 0.2488
6/8 [=====================>........] - ETA: 0s - loss: 13.1540 - accuracy: 0.2140
7/8 [=========================>....] - ETA: 0s - loss: 12.8530 - accuracy: 0.2171
8/8 [==============================] - 1s 71ms/step - loss: 12.7866 - accuracy: 0.2338
8/8 [==============================] - 1s 94ms/step - loss: 12.7866 - accuracy: 0.2338 - val_loss: 11.0351 - val_accuracy: 0.3540
Epoch 79/100
1/8 [==>...........................] - ETA: 0s - loss: 10.6588 - accuracy: 0.3530
2/8 [======>.......................] - ETA: 0s - loss: 11.2097 - accuracy: 0.1820
3/8 [==========>...................] - ETA: 0s - loss: 10.3940 - accuracy: 0.1967
4/8 [==============>...............] - ETA: 0s - loss: 10.3659 - accuracy: 0.1577
5/8 [=================>............] - ETA: 0s - loss: 10.4442 - accuracy: 0.1938
6/8 [=====================>........] - ETA: 0s - loss: 10.6223 - accuracy: 0.2197
7/8 [=========================>....] - ETA: 0s - loss: 10.7018 - accuracy: 0.2170
8/8 [==============================] - 1s 71ms/step - loss: 10.8460 - accuracy: 0.1964
8/8 [==============================] - 1s 94ms/step - loss: 10.8460 - accuracy: 0.1964 - val_loss: 12.0121 - val_accuracy: 0.3540
Epoch 80/100
1/8 [==>...........................] - ETA: 0s - loss: 11.3201 - accuracy: 0.3600
2/8 [======>.......................] - ETA: 0s - loss: 11.1304 - accuracy: 0.3565
3/8 [==========>...................] - ETA: 0s - loss: 11.2072 - accuracy: 0.3537
4/8 [==============>...............] - ETA: 0s - loss: 11.2071 - accuracy: 0.3248
5/8 [=================>............] - ETA: 0s - loss: 10.9331 - accuracy: 0.3046
6/8 [=====================>........] - ETA: 0s - loss: 11.0842 - accuracy: 0.3107
7/8 [=========================>....] - ETA: 0s - loss: 11.1297 - accuracy: 0.2736
8/8 [==============================] - 1s 74ms/step - loss: 11.0390 - accuracy: 0.2853
8/8 [==============================] - 1s 96ms/step - loss: 11.0390 - accuracy: 0.2853 - val_loss: 9.6399 - val_accuracy: 0.2220
Epoch 81/100
1/8 [==>...........................] - ETA: 0s - loss: 10.5653 - accuracy: 0.2260
2/8 [======>.......................] - ETA: 0s - loss: 10.3415 - accuracy: 0.1150
3/8 [==========>...................] - ETA: 0s - loss: 9.9737 - accuracy: 0.1907
4/8 [==============>...............] - ETA: 0s - loss: 9.9155 - accuracy: 0.2323
5/8 [=================>............] - ETA: 0s - loss: 9.9715 - accuracy: 0.2306
6/8 [=====================>........] - ETA: 0s - loss: 9.9038 - accuracy: 0.2013
7/8 [=========================>....] - ETA: 0s - loss: 9.7410 - accuracy: 0.2250
8/8 [==============================] - 1s 72ms/step - loss: 9.4964 - accuracy: 0.2245
8/8 [==============================] - 1s 95ms/step - loss: 9.4964 - accuracy: 0.2245 - val_loss: 8.5634 - val_accuracy: 0.2220
Epoch 82/100
1/8 [==>...........................] - ETA: 0s - loss: 8.4646 - accuracy: 0.2040
2/8 [======>.......................] - ETA: 0s - loss: 7.9227 - accuracy: 0.2885
3/8 [==========>...................] - ETA: 0s - loss: 8.6195 - accuracy: 0.2097
4/8 [==============>...............] - ETA: 0s - loss: 8.5758 - accuracy: 0.1660
5/8 [=================>............] - ETA: 0s - loss: 8.4546 - accuracy: 0.1994
6/8 [=====================>........] - ETA: 0s - loss: 8.3109 - accuracy: 0.2045
7/8 [=========================>....] - ETA: 0s - loss: 8.5037 - accuracy: 0.2227
8/8 [==============================] - 1s 70ms/step - loss: 8.7392 - accuracy: 0.2380
8/8 [==============================] - 1s 92ms/step - loss: 8.7392 - accuracy: 0.2380 - val_loss: 9.2382 - val_accuracy: 0.3540
Epoch 83/100
1/8 [==>...........................] - ETA: 0s - loss: 9.6861 - accuracy: 0.3340
2/8 [======>.......................] - ETA: 0s - loss: 9.2691 - accuracy: 0.2720
3/8 [==========>...................] - ETA: 0s - loss: 8.8562 - accuracy: 0.2620
4/8 [==============>...............] - ETA: 0s - loss: 8.9816 - accuracy: 0.2873
5/8 [=================>............] - ETA: 0s - loss: 8.9471 - accuracy: 0.2310
6/8 [=====================>........] - ETA: 0s - loss: 8.8307 - accuracy: 0.2527
7/8 [=========================>....] - ETA: 0s - loss: 8.6947 - accuracy: 0.2469
8/8 [==============================] - 1s 77ms/step - loss: 8.7208 - accuracy: 0.2586
8/8 [==============================] - 1s 101ms/step - loss: 8.7208 - accuracy: 0.2586 - val_loss: 8.0472 - val_accuracy: 0.3540
Epoch 84/100
1/8 [==>...........................] - ETA: 0s - loss: 8.9494 - accuracy: 0.3580
2/8 [======>.......................] - ETA: 0s - loss: 8.2941 - accuracy: 0.2835
3/8 [==========>...................] - ETA: 0s - loss: 7.9222 - accuracy: 0.2677
4/8 [==============>...............] - ETA: 0s - loss: 7.8446 - accuracy: 0.2830
5/8 [=================>............] - ETA: 0s - loss: 7.8895 - accuracy: 0.2362
6/8 [=====================>........] - ETA: 0s - loss: 7.7364 - accuracy: 0.2553
7/8 [=========================>....] - ETA: 0s - loss: 7.7180 - accuracy: 0.2477
8/8 [==============================] - 1s 75ms/step - loss: 7.7255 - accuracy: 0.2616
8/8 [==============================] - 1s 97ms/step - loss: 7.7255 - accuracy: 0.2616 - val_loss: 7.6665 - val_accuracy: 0.3540
Epoch 85/100
1/8 [==>...........................] - ETA: 0s - loss: 7.6964 - accuracy: 0.3440
2/8 [======>.......................] - ETA: 0s - loss: 7.4027 - accuracy: 0.2790
3/8 [==========>...................] - ETA: 0s - loss: 7.8431 - accuracy: 0.2557
4/8 [==============>...............] - ETA: 0s - loss: 7.8678 - accuracy: 0.2760
5/8 [=================>............] - ETA: 0s - loss: 7.9447 - accuracy: 0.2900
6/8 [=====================>........] - ETA: 0s - loss: 7.7295 - accuracy: 0.2787
7/8 [=========================>....] - ETA: 0s - loss: 7.4415 - accuracy: 0.2876
8/8 [==============================] - 1s 76ms/step - loss: 7.4554 - accuracy: 0.2949
8/8 [==============================] - 1s 99ms/step - loss: 7.4554 - accuracy: 0.2949 - val_loss: 6.2801 - val_accuracy: 0.3540
Epoch 86/100
1/8 [==>...........................] - ETA: 0s - loss: 6.3243 - accuracy: 0.3360
2/8 [======>.......................] - ETA: 0s - loss: 6.8157 - accuracy: 0.3425
3/8 [==========>...................] - ETA: 0s - loss: 6.5607 - accuracy: 0.3377
4/8 [==============>...............] - ETA: 0s - loss: 6.5733 - accuracy: 0.3400
5/8 [=================>............] - ETA: 0s - loss: 6.7182 - accuracy: 0.2794
6/8 [=====================>........] - ETA: 0s - loss: 6.5752 - accuracy: 0.2917
7/8 [=========================>....] - ETA: 0s - loss: 6.6198 - accuracy: 0.3036
8/8 [==============================] - 1s 78ms/step - loss: 6.6150 - accuracy: 0.2910
8/8 [==============================] - 1s 102ms/step - loss: 6.6150 - accuracy: 0.2910 - val_loss: 6.8386 - val_accuracy: 0.3540
Epoch 87/100
1/8 [==>...........................] - ETA: 0s - loss: 6.8651 - accuracy: 0.3420
2/8 [======>.......................] - ETA: 0s - loss: 7.0159 - accuracy: 0.3450
3/8 [==========>...................] - ETA: 0s - loss: 7.0390 - accuracy: 0.2527
4/8 [==============>...............] - ETA: 0s - loss: 7.0382 - accuracy: 0.2752
5/8 [=================>............] - ETA: 0s - loss: 7.1507 - accuracy: 0.2634
6/8 [=====================>........] - ETA: 0s - loss: 7.1935 - accuracy: 0.2812
7/8 [=========================>....] - ETA: 0s - loss: 7.1397 - accuracy: 0.2907
8/8 [==============================] - 1s 86ms/step - loss: 7.2180 - accuracy: 0.2560
8/8 [==============================] - 1s 109ms/step - loss: 7.2180 - accuracy: 0.2560 - val_loss: 6.0512 - val_accuracy: 0.2220
Epoch 88/100
1/8 [==>...........................] - ETA: 0s - loss: 7.1514 - accuracy: 0.2160
2/8 [======>.......................] - ETA: 0s - loss: 6.7202 - accuracy: 0.2865
3/8 [==========>...................] - ETA: 0s - loss: 6.5132 - accuracy: 0.3040
4/8 [==============>...............] - ETA: 0s - loss: 6.1972 - accuracy: 0.2837
5/8 [=================>............] - ETA: 0s - loss: 6.0809 - accuracy: 0.2704
6/8 [=====================>........] - ETA: 0s - loss: 5.9472 - accuracy: 0.2797
7/8 [=========================>....] - ETA: 0s - loss: 5.8184 - accuracy: 0.2476
8/8 [==============================] - 1s 81ms/step - loss: 5.9233 - accuracy: 0.2217
8/8 [==============================] - 1s 103ms/step - loss: 5.9233 - accuracy: 0.2217 - val_loss: 5.3708 - val_accuracy: 0.3540
Epoch 89/100
1/8 [==>...........................] - ETA: 0s - loss: 6.1778 - accuracy: 0.3530
2/8 [======>.......................] - ETA: 0s - loss: 6.2421 - accuracy: 0.3565
3/8 [==========>...................] - ETA: 0s - loss: 6.4908 - accuracy: 0.3103
4/8 [==============>...............] - ETA: 0s - loss: 6.4019 - accuracy: 0.2415
5/8 [=================>............] - ETA: 0s - loss: 6.2213 - accuracy: 0.2630
6/8 [=====================>........] - ETA: 0s - loss: 6.2914 - accuracy: 0.2752
7/8 [=========================>....] - ETA: 0s - loss: 6.3158 - accuracy: 0.2697
8/8 [==============================] - 1s 75ms/step - loss: 6.3495 - accuracy: 0.2402
8/8 [==============================] - 1s 98ms/step - loss: 6.3495 - accuracy: 0.2402 - val_loss: 6.6930 - val_accuracy: 0.3540
Epoch 90/100
1/8 [==>...........................] - ETA: 0s - loss: 7.4425 - accuracy: 0.3600
2/8 [======>.......................] - ETA: 0s - loss: 6.9272 - accuracy: 0.3540
3/8 [==========>...................] - ETA: 0s - loss: 6.9678 - accuracy: 0.3053
4/8 [==============>...............] - ETA: 0s - loss: 6.7934 - accuracy: 0.3170
5/8 [=================>............] - ETA: 0s - loss: 6.7949 - accuracy: 0.3226
6/8 [=====================>........] - ETA: 0s - loss: 6.6807 - accuracy: 0.3253
7/8 [=========================>....] - ETA: 0s - loss: 6.6300 - accuracy: 0.3107
8/8 [==============================] - 1s 76ms/step - loss: 6.4216 - accuracy: 0.3156
8/8 [==============================] - 1s 98ms/step - loss: 6.4216 - accuracy: 0.3156 - val_loss: 5.1521 - val_accuracy: 0.3540
Epoch 91/100
1/8 [==>...........................] - ETA: 0s - loss: 5.6178 - accuracy: 0.3540
2/8 [======>.......................] - ETA: 0s - loss: 5.1876 - accuracy: 0.3505
3/8 [==========>...................] - ETA: 0s - loss: 5.0753 - accuracy: 0.3000
4/8 [==============>...............] - ETA: 0s - loss: 5.0486 - accuracy: 0.2370
5/8 [=================>............] - ETA: 0s - loss: 4.9910 - accuracy: 0.2644
6/8 [=====================>........] - ETA: 0s - loss: 4.9773 - accuracy: 0.2787
7/8 [=========================>....] - ETA: 0s - loss: 4.9690 - accuracy: 0.2716
8/8 [==============================] - 1s 82ms/step - loss: 4.9226 - accuracy: 0.2794
8/8 [==============================] - 1s 104ms/step - loss: 4.9226 - accuracy: 0.2794 - val_loss: 4.6313 - val_accuracy: 0.3540
Epoch 92/100
1/8 [==>...........................] - ETA: 0s - loss: 4.9819 - accuracy: 0.3330
2/8 [======>.......................] - ETA: 0s - loss: 4.6728 - accuracy: 0.3470
3/8 [==========>...................] - ETA: 0s - loss: 4.6979 - accuracy: 0.2957
4/8 [==============>...............] - ETA: 0s - loss: 4.4624 - accuracy: 0.3095
5/8 [=================>............] - ETA: 0s - loss: 4.2700 - accuracy: 0.3192
6/8 [=====================>........] - ETA: 0s - loss: 4.1391 - accuracy: 0.2748
7/8 [=========================>....] - ETA: 0s - loss: 4.0548 - accuracy: 0.2686
8/8 [==============================] - 1s 74ms/step - loss: 4.0431 - accuracy: 0.2765
8/8 [==============================] - 1s 96ms/step - loss: 4.0431 - accuracy: 0.2765 - val_loss: 3.3797 - val_accuracy: 0.3540
Epoch 93/100
1/8 [==>...........................] - ETA: 0s - loss: 3.5205 - accuracy: 0.3630
2/8 [======>.......................] - ETA: 0s - loss: 3.4538 - accuracy: 0.2110
3/8 [==========>...................] - ETA: 0s - loss: 3.4876 - accuracy: 0.1433
4/8 [==============>...............] - ETA: 0s - loss: 3.4987 - accuracy: 0.1893
5/8 [=================>............] - ETA: 0s - loss: 3.4847 - accuracy: 0.1932
6/8 [=====================>........] - ETA: 0s - loss: 3.4804 - accuracy: 0.2197
7/8 [=========================>....] - ETA: 0s - loss: 3.5134 - accuracy: 0.2374
8/8 [==============================] - 1s 76ms/step - loss: 3.5121 - accuracy: 0.2529
8/8 [==============================] - 1s 100ms/step - loss: 3.5121 - accuracy: 0.2529 - val_loss: 3.4666 - val_accuracy: 0.2220
Epoch 94/100
1/8 [==>...........................] - ETA: 0s - loss: 4.0003 - accuracy: 0.2040
2/8 [======>.......................] - ETA: 0s - loss: 4.1141 - accuracy: 0.2820
3/8 [==========>...................] - ETA: 0s - loss: 3.8202 - accuracy: 0.3083
4/8 [==============>...............] - ETA: 0s - loss: 3.9596 - accuracy: 0.3113
5/8 [=================>............] - ETA: 0s - loss: 3.8751 - accuracy: 0.2938
6/8 [=====================>........] - ETA: 0s - loss: 3.7680 - accuracy: 0.3038
7/8 [=========================>....] - ETA: 0s - loss: 3.7922 - accuracy: 0.3121
8/8 [==============================] - 1s 82ms/step - loss: 3.7359 - accuracy: 0.3011
8/8 [==============================] - 1s 105ms/step - loss: 3.7359 - accuracy: 0.3011 - val_loss: 3.4136 - val_accuracy: 0.0080
Epoch 95/100
1/8 [==>...........................] - ETA: 0s - loss: 3.8448 - accuracy: 0.0090
2/8 [======>.......................] - ETA: 0s - loss: 3.7593 - accuracy: 0.1790
3/8 [==========>...................] - ETA: 0s - loss: 3.6905 - accuracy: 0.2367
4/8 [==============>...............] - ETA: 0s - loss: 3.7770 - accuracy: 0.2310
5/8 [=================>............] - ETA: 0s - loss: 3.7308 - accuracy: 0.2530
6/8 [=====================>........] - ETA: 0s - loss: 3.7626 - accuracy: 0.2750
7/8 [=========================>....] - ETA: 0s - loss: 3.7686 - accuracy: 0.2869
8/8 [==============================] - 1s 74ms/step - loss: 3.7481 - accuracy: 0.2925
8/8 [==============================] - 1s 98ms/step - loss: 3.7481 - accuracy: 0.2925 - val_loss: 3.3103 - val_accuracy: 0.3540
Epoch 96/100
1/8 [==>...........................] - ETA: 0s - loss: 3.6429 - accuracy: 0.3480
2/8 [======>.......................] - ETA: 0s - loss: 3.8693 - accuracy: 0.3435
3/8 [==========>...................] - ETA: 0s - loss: 3.7710 - accuracy: 0.3520
4/8 [==============>...............] - ETA: 0s - loss: 3.6916 - accuracy: 0.3517
5/8 [=================>............] - ETA: 0s - loss: 3.6723 - accuracy: 0.3516
6/8 [=====================>........] - ETA: 0s - loss: 3.6699 - accuracy: 0.3537
7/8 [=========================>....] - ETA: 0s - loss: 3.6360 - accuracy: 0.3539
8/8 [==============================] - 1s 76ms/step - loss: 3.5908 - accuracy: 0.3514
8/8 [==============================] - 1s 99ms/step - loss: 3.5908 - accuracy: 0.3514 - val_loss: 3.1797 - val_accuracy: 0.2220
Epoch 97/100
1/8 [==>...........................] - ETA: 0s - loss: 3.5412 - accuracy: 0.2270
2/8 [======>.......................] - ETA: 0s - loss: 3.4831 - accuracy: 0.2840
3/8 [==========>...................] - ETA: 0s - loss: 3.5119 - accuracy: 0.3057
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8/8 [==============================] - 1s 81ms/step - loss: 3.1726 - accuracy: 0.3195
8/8 [==============================] - 1s 105ms/step - loss: 3.1726 - accuracy: 0.3195 - val_loss: 2.7900 - val_accuracy: 0.3540
Epoch 98/100
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8/8 [==============================] - 1s 78ms/step - loss: 3.0273 - accuracy: 0.2745
8/8 [==============================] - 1s 101ms/step - loss: 3.0273 - accuracy: 0.2745 - val_loss: 2.9103 - val_accuracy: 0.3540
Epoch 99/100
1/8 [==>...........................] - ETA: 0s - loss: 3.2530 - accuracy: 0.3610
2/8 [======>.......................] - ETA: 0s - loss: 3.1417 - accuracy: 0.2970
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7/8 [=========================>....] - ETA: 0s - loss: 3.5337 - accuracy: 0.3237
8/8 [==============================] - 1s 77ms/step - loss: 3.6293 - accuracy: 0.3271
8/8 [==============================] - 1s 99ms/step - loss: 3.6293 - accuracy: 0.3271 - val_loss: 3.2801 - val_accuracy: 0.2220
Epoch 100/100
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2/8 [======>.......................] - ETA: 0s - loss: 3.5455 - accuracy: 0.2990
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6/8 [=====================>........] - ETA: 0s - loss: 3.9021 - accuracy: 0.2885
7/8 [=========================>....] - ETA: 0s - loss: 3.8630 - accuracy: 0.2986
8/8 [==============================] - 1s 71ms/step - loss: 3.8770 - accuracy: 0.2892
8/8 [==============================] - 1s 93ms/step - loss: 3.8770 - accuracy: 0.2892 - val_loss: 3.1812 - val_accuracy: 0.2220
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-18-15Z
Training run 6/8 (flags = list(392, 0.05, 200, 30, "tanh"))
Using run directory runs/2020-11-02T21-19-46Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/30
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13/40 [========>.....................] - ETA: 0s - loss: 17.5879 - accuracy: 0.1550
15/40 [==========>...................] - ETA: 0s - loss: 20.0189 - accuracy: 0.1580
17/40 [===========>..................] - ETA: 0s - loss: 21.7520 - accuracy: 0.1400
19/40 [=============>................] - ETA: 0s - loss: 23.0764 - accuracy: 0.1358
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23/40 [================>.............] - ETA: 0s - loss: 25.2385 - accuracy: 0.1291
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27/40 [===================>..........] - ETA: 0s - loss: 26.2194 - accuracy: 0.1496
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31/40 [======================>.......] - ETA: 0s - loss: 27.0823 - accuracy: 0.1495
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35/40 [=========================>....] - ETA: 0s - loss: 27.3278 - accuracy: 0.1483
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39/40 [============================>.] - ETA: 0s - loss: 26.9351 - accuracy: 0.1510
40/40 [==============================] - 1s 26ms/step - loss: 26.8651 - accuracy: 0.1488
40/40 [==============================] - 2s 43ms/step - loss: 26.8651 - accuracy: 0.1488 - val_loss: 22.8957 - val_accuracy: 0.0470
Epoch 2/30
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4/40 [==>...........................] - ETA: 0s - loss: 21.9413 - accuracy: 0.2812
7/40 [====>.........................] - ETA: 0s - loss: 22.3868 - accuracy: 0.2064
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14/40 [=========>....................] - ETA: 0s - loss: 21.6027 - accuracy: 0.2175
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31/40 [======================>.......] - ETA: 0s - loss: 18.1738 - accuracy: 0.2123
33/40 [=======================>......] - ETA: 0s - loss: 17.9861 - accuracy: 0.2170
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39/40 [============================>.] - ETA: 0s - loss: 17.3221 - accuracy: 0.2060
40/40 [==============================] - 1s 25ms/step - loss: 17.1219 - accuracy: 0.2111
40/40 [==============================] - 1s 31ms/step - loss: 17.1219 - accuracy: 0.2111 - val_loss: 11.5567 - val_accuracy: 0.3540
Epoch 3/30
1/40 [..............................] - ETA: 0s - loss: 11.2374 - accuracy: 0.3500
3/40 [=>............................] - ETA: 0s - loss: 12.3434 - accuracy: 0.2983
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21/40 [==============>...............] - ETA: 0s - loss: 11.1060 - accuracy: 0.2383
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40/40 [==============================] - 1s 31ms/step - loss: 9.6907 - accuracy: 0.2663
40/40 [==============================] - 1s 36ms/step - loss: 9.6907 - accuracy: 0.2663 - val_loss: 6.5444 - val_accuracy: 0.3540
Epoch 4/30
1/40 [..............................] - ETA: 0s - loss: 6.5468 - accuracy: 0.3650
3/40 [=>............................] - ETA: 0s - loss: 6.3847 - accuracy: 0.3133
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40/40 [==============================] - 1s 25ms/step - loss: 5.7686 - accuracy: 0.2705
40/40 [==============================] - 1s 30ms/step - loss: 5.7686 - accuracy: 0.2705 - val_loss: 6.5128 - val_accuracy: 0.3540
Epoch 5/30
1/40 [..............................] - ETA: 0s - loss: 5.1324 - accuracy: 0.3400
4/40 [==>...........................] - ETA: 0s - loss: 5.6677 - accuracy: 0.3762
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38/40 [===========================>..] - ETA: 0s - loss: 7.4996 - accuracy: 0.2643
40/40 [==============================] - 1s 25ms/step - loss: 7.5884 - accuracy: 0.2694
40/40 [==============================] - 1s 30ms/step - loss: 7.5884 - accuracy: 0.2694 - val_loss: 9.3075 - val_accuracy: 0.3540
Epoch 6/30
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3/40 [=>............................] - ETA: 0s - loss: 7.3946 - accuracy: 0.2100
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15/40 [==========>...................] - ETA: 0s - loss: 8.0567 - accuracy: 0.2243
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40/40 [==============================] - 1s 27ms/step - loss: 8.9799 - accuracy: 0.2319
40/40 [==============================] - 1s 32ms/step - loss: 8.9799 - accuracy: 0.2319 - val_loss: 8.2531 - val_accuracy: 0.3540
Epoch 7/30
1/40 [..............................] - ETA: 0s - loss: 6.8011 - accuracy: 0.3250
3/40 [=>............................] - ETA: 0s - loss: 7.6174 - accuracy: 0.1483
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40/40 [==============================] - 1s 27ms/step - loss: 8.9376 - accuracy: 0.2105
40/40 [==============================] - 1s 31ms/step - loss: 8.9376 - accuracy: 0.2105 - val_loss: 10.4889 - val_accuracy: 0.3540
Epoch 8/30
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40/40 [==============================] - 1s 27ms/step - loss: 8.1607 - accuracy: 0.2103
40/40 [==============================] - 1s 32ms/step - loss: 8.1607 - accuracy: 0.2103 - val_loss: 11.2679 - val_accuracy: 0.3540
Epoch 9/30
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3/40 [=>............................] - ETA: 0s - loss: 11.7489 - accuracy: 0.3283
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40/40 [==============================] - 1s 27ms/step - loss: 9.3379 - accuracy: 0.2137
40/40 [==============================] - 1s 32ms/step - loss: 9.3379 - accuracy: 0.2137 - val_loss: 6.0399 - val_accuracy: 0.0250
Epoch 10/30
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40/40 [==============================] - 1s 27ms/step - loss: 6.1973 - accuracy: 0.2538
40/40 [==============================] - 1s 32ms/step - loss: 6.1973 - accuracy: 0.2538 - val_loss: 5.3689 - val_accuracy: 0.2220
Epoch 11/30
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40/40 [==============================] - 1s 27ms/step - loss: 6.5969 - accuracy: 0.2258
40/40 [==============================] - 1s 32ms/step - loss: 6.5969 - accuracy: 0.2258 - val_loss: 5.9849 - val_accuracy: 0.3540
Epoch 12/30
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40/40 [==============================] - 1s 27ms/step - loss: 6.6087 - accuracy: 0.2669
40/40 [==============================] - 1s 32ms/step - loss: 6.6087 - accuracy: 0.2669 - val_loss: 6.6327 - val_accuracy: 0.3540
Epoch 13/30
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40/40 [==============================] - 1s 28ms/step - loss: 5.5809 - accuracy: 0.2403
40/40 [==============================] - 1s 33ms/step - loss: 5.5809 - accuracy: 0.2403 - val_loss: 6.0365 - val_accuracy: 0.3540
Epoch 14/30
1/40 [..............................] - ETA: 0s - loss: 6.5810 - accuracy: 0.3250
3/40 [=>............................] - ETA: 0s - loss: 7.0377 - accuracy: 0.2350
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40/40 [==============================] - 1s 27ms/step - loss: 5.3980 - accuracy: 0.2562
40/40 [==============================] - 1s 32ms/step - loss: 5.3980 - accuracy: 0.2562 - val_loss: 4.8387 - val_accuracy: 0.0250
Epoch 15/30
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40/40 [==============================] - 1s 28ms/step - loss: 4.7163 - accuracy: 0.2306
40/40 [==============================] - 1s 33ms/step - loss: 4.7163 - accuracy: 0.2306 - val_loss: 4.3605 - val_accuracy: 0.0440
Epoch 16/30
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40/40 [==============================] - 1s 27ms/step - loss: 5.0050 - accuracy: 0.2435
40/40 [==============================] - 1s 32ms/step - loss: 5.0050 - accuracy: 0.2435 - val_loss: 4.0381 - val_accuracy: 0.3540
Epoch 17/30
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40/40 [==============================] - 1s 28ms/step - loss: 3.9684 - accuracy: 0.3001
40/40 [==============================] - 1s 33ms/step - loss: 3.9684 - accuracy: 0.3001 - val_loss: 3.9379 - val_accuracy: 0.3540
Epoch 18/30
1/40 [..............................] - ETA: 0s - loss: 5.3091 - accuracy: 0.3050
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40/40 [==============================] - 1s 27ms/step - loss: 3.8021 - accuracy: 0.2895
40/40 [==============================] - 1s 32ms/step - loss: 3.8021 - accuracy: 0.2895 - val_loss: 4.1261 - val_accuracy: 0.3540
Epoch 19/30
1/40 [..............................] - ETA: 0s - loss: 4.8498 - accuracy: 0.3000
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40/40 [==============================] - 1s 27ms/step - loss: 3.9693 - accuracy: 0.2930
40/40 [==============================] - 1s 32ms/step - loss: 3.9693 - accuracy: 0.2930 - val_loss: 4.5189 - val_accuracy: 0.2220
Epoch 20/30
1/40 [..............................] - ETA: 0s - loss: 5.0565 - accuracy: 0.2400
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40/40 [==============================] - 1s 26ms/step - loss: 5.3858 - accuracy: 0.2633
40/40 [==============================] - 1s 31ms/step - loss: 5.3858 - accuracy: 0.2633 - val_loss: 5.2863 - val_accuracy: 0.3540
Epoch 21/30
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40/40 [==============================] - 1s 27ms/step - loss: 8.6823 - accuracy: 0.2017
40/40 [==============================] - 1s 32ms/step - loss: 8.6823 - accuracy: 0.2017 - val_loss: 7.4299 - val_accuracy: 0.0150
Epoch 22/30
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40/40 [==============================] - 1s 25ms/step - loss: 12.1244 - accuracy: 0.2121
40/40 [==============================] - 1s 30ms/step - loss: 12.1244 - accuracy: 0.2121 - val_loss: 19.4633 - val_accuracy: 0.3540
Epoch 23/30
1/40 [..............................] - ETA: 0s - loss: 15.6004 - accuracy: 0.3250
3/40 [=>............................] - ETA: 0s - loss: 19.7941 - accuracy: 0.3367
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38/40 [===========================>..] - ETA: 0s - loss: 15.0776 - accuracy: 0.2374
40/40 [==============================] - 1s 27ms/step - loss: 14.9963 - accuracy: 0.2325
40/40 [==============================] - 1s 32ms/step - loss: 14.9963 - accuracy: 0.2325 - val_loss: 14.7184 - val_accuracy: 0.3540
Epoch 24/30
1/40 [..............................] - ETA: 0s - loss: 14.7074 - accuracy: 0.2850
3/40 [=>............................] - ETA: 0s - loss: 12.5396 - accuracy: 0.2900
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8/40 [=====>........................] - ETA: 0s - loss: 13.3266 - accuracy: 0.2481
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16/40 [===========>..................] - ETA: 0s - loss: 13.0653 - accuracy: 0.2484
18/40 [============>.................] - ETA: 0s - loss: 12.6590 - accuracy: 0.2419
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25/40 [=================>............] - ETA: 0s - loss: 12.0326 - accuracy: 0.2256
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30/40 [=====================>........] - ETA: 0s - loss: 12.4929 - accuracy: 0.2190
32/40 [=======================>......] - ETA: 0s - loss: 12.6638 - accuracy: 0.2166
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38/40 [===========================>..] - ETA: 0s - loss: 13.0803 - accuracy: 0.2232
40/40 [==============================] - 1s 26ms/step - loss: 13.2075 - accuracy: 0.2223
40/40 [==============================] - 1s 31ms/step - loss: 13.2075 - accuracy: 0.2223 - val_loss: 17.2724 - val_accuracy: 0.3540
Epoch 25/30
1/40 [..............................] - ETA: 0s - loss: 17.0725 - accuracy: 0.4000
3/40 [=>............................] - ETA: 0s - loss: 16.4226 - accuracy: 0.3133
5/40 [==>...........................] - ETA: 0s - loss: 16.4181 - accuracy: 0.2620
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15/40 [==========>...................] - ETA: 0s - loss: 16.3189 - accuracy: 0.2187
17/40 [===========>..................] - ETA: 0s - loss: 16.7401 - accuracy: 0.2124
19/40 [=============>................] - ETA: 0s - loss: 16.9585 - accuracy: 0.2050
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23/40 [================>.............] - ETA: 0s - loss: 17.1206 - accuracy: 0.2089
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27/40 [===================>..........] - ETA: 0s - loss: 16.9966 - accuracy: 0.2130
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31/40 [======================>.......] - ETA: 0s - loss: 17.0038 - accuracy: 0.2090
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39/40 [============================>.] - ETA: 0s - loss: 17.0388 - accuracy: 0.1965
40/40 [==============================] - 1s 26ms/step - loss: 16.9297 - accuracy: 0.2002
40/40 [==============================] - 1s 31ms/step - loss: 16.9297 - accuracy: 0.2002 - val_loss: 16.7036 - val_accuracy: 0.3540
Epoch 26/30
1/40 [..............................] - ETA: 0s - loss: 12.6242 - accuracy: 0.3800
3/40 [=>............................] - ETA: 0s - loss: 15.7135 - accuracy: 0.1550
5/40 [==>...........................] - ETA: 0s - loss: 17.2419 - accuracy: 0.2020
8/40 [=====>........................] - ETA: 0s - loss: 16.9020 - accuracy: 0.2219
10/40 [======>.......................] - ETA: 0s - loss: 17.5435 - accuracy: 0.2275
12/40 [========>.....................] - ETA: 0s - loss: 18.1287 - accuracy: 0.2192
14/40 [=========>....................] - ETA: 0s - loss: 18.0576 - accuracy: 0.2304
16/40 [===========>..................] - ETA: 0s - loss: 18.0189 - accuracy: 0.2047
18/40 [============>.................] - ETA: 0s - loss: 18.2703 - accuracy: 0.2050
20/40 [==============>...............] - ETA: 0s - loss: 18.5321 - accuracy: 0.2130
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24/40 [=================>............] - ETA: 0s - loss: 18.5290 - accuracy: 0.2029
27/40 [===================>..........] - ETA: 0s - loss: 18.4775 - accuracy: 0.1974
29/40 [====================>.........] - ETA: 0s - loss: 18.1994 - accuracy: 0.2038
31/40 [======================>.......] - ETA: 0s - loss: 18.0911 - accuracy: 0.2042
33/40 [=======================>......] - ETA: 0s - loss: 17.9226 - accuracy: 0.1995
35/40 [=========================>....] - ETA: 0s - loss: 17.9256 - accuracy: 0.1891
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40/40 [==============================] - 1s 26ms/step - loss: 18.0194 - accuracy: 0.1850
40/40 [==============================] - 1s 31ms/step - loss: 18.0194 - accuracy: 0.1850 - val_loss: 16.6369 - val_accuracy: 0.0440
Epoch 27/30
1/40 [..............................] - ETA: 0s - loss: 16.1759 - accuracy: 0.0450
3/40 [=>............................] - ETA: 0s - loss: 16.6308 - accuracy: 0.2417
5/40 [==>...........................] - ETA: 0s - loss: 16.4707 - accuracy: 0.1980
8/40 [=====>........................] - ETA: 0s - loss: 16.5008 - accuracy: 0.1994
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15/40 [==========>...................] - ETA: 0s - loss: 15.9525 - accuracy: 0.1930
17/40 [===========>..................] - ETA: 0s - loss: 15.7526 - accuracy: 0.1903
19/40 [=============>................] - ETA: 0s - loss: 15.7752 - accuracy: 0.1882
21/40 [==============>...............] - ETA: 0s - loss: 16.1486 - accuracy: 0.1764
23/40 [================>.............] - ETA: 0s - loss: 16.5321 - accuracy: 0.1839
25/40 [=================>............] - ETA: 0s - loss: 16.8801 - accuracy: 0.1922
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29/40 [====================>.........] - ETA: 0s - loss: 17.0616 - accuracy: 0.1981
31/40 [======================>.......] - ETA: 0s - loss: 17.1463 - accuracy: 0.1971
33/40 [=======================>......] - ETA: 0s - loss: 17.1794 - accuracy: 0.1923
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40/40 [==============================] - 1s 27ms/step - loss: 16.8680 - accuracy: 0.2006
40/40 [==============================] - 1s 32ms/step - loss: 16.8680 - accuracy: 0.2006 - val_loss: 16.3687 - val_accuracy: 0.2220
Epoch 28/30
1/40 [..............................] - ETA: 0s - loss: 19.9767 - accuracy: 0.2200
3/40 [=>............................] - ETA: 0s - loss: 17.1245 - accuracy: 0.1883
5/40 [==>...........................] - ETA: 0s - loss: 16.1446 - accuracy: 0.2170
7/40 [====>.........................] - ETA: 0s - loss: 17.1680 - accuracy: 0.2071
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13/40 [========>.....................] - ETA: 0s - loss: 16.4191 - accuracy: 0.2712
15/40 [==========>...................] - ETA: 0s - loss: 16.3034 - accuracy: 0.2690
17/40 [===========>..................] - ETA: 0s - loss: 16.2388 - accuracy: 0.2603
19/40 [=============>................] - ETA: 0s - loss: 15.6992 - accuracy: 0.2521
21/40 [==============>...............] - ETA: 0s - loss: 15.5217 - accuracy: 0.2552
23/40 [================>.............] - ETA: 0s - loss: 15.4120 - accuracy: 0.2472
25/40 [=================>............] - ETA: 0s - loss: 15.4245 - accuracy: 0.2376
27/40 [===================>..........] - ETA: 0s - loss: 14.9852 - accuracy: 0.2470
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40/40 [==============================] - 1s 27ms/step - loss: 14.9828 - accuracy: 0.2403
40/40 [==============================] - 1s 32ms/step - loss: 14.9828 - accuracy: 0.2403 - val_loss: 15.2950 - val_accuracy: 0.0590
Epoch 29/30
1/40 [..............................] - ETA: 0s - loss: 16.7000 - accuracy: 0.0900
3/40 [=>............................] - ETA: 0s - loss: 15.0669 - accuracy: 0.1550
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16/40 [===========>..................] - ETA: 0s - loss: 13.2555 - accuracy: 0.1719
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20/40 [==============>...............] - ETA: 0s - loss: 12.9370 - accuracy: 0.1863
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40/40 [==============================] - 1s 27ms/step - loss: 13.3919 - accuracy: 0.2088
40/40 [==============================] - 1s 32ms/step - loss: 13.3919 - accuracy: 0.2088 - val_loss: 13.0993 - val_accuracy: 0.3540
Epoch 30/30
1/40 [..............................] - ETA: 0s - loss: 11.8962 - accuracy: 0.2900
4/40 [==>...........................] - ETA: 0s - loss: 12.1829 - accuracy: 0.2625
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21/40 [==============>...............] - ETA: 0s - loss: 12.2579 - accuracy: 0.2238
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38/40 [===========================>..] - ETA: 0s - loss: 11.4906 - accuracy: 0.2155
40/40 [==============================] - 1s 26ms/step - loss: 11.4912 - accuracy: 0.2190
40/40 [==============================] - 1s 30ms/step - loss: 11.4912 - accuracy: 0.2190 - val_loss: 11.9062 - val_accuracy: 0.3540
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-19-46Z
Training run 7/8 (flags = list(64, 1e-04, 200, 100, "relu"))
Using run directory runs/2020-11-02T21-20-26Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/100
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9/40 [=====>........................] - ETA: 0s - loss: 3.8139 - accuracy: 0.0311
16/40 [===========>..................] - ETA: 0s - loss: 3.8014 - accuracy: 0.0647
23/40 [================>.............] - ETA: 0s - loss: 3.7888 - accuracy: 0.1057
30/40 [=====================>........] - ETA: 0s - loss: 3.7734 - accuracy: 0.1483
38/40 [===========================>..] - ETA: 0s - loss: 3.7530 - accuracy: 0.1824
40/40 [==============================] - 0s 7ms/step - loss: 3.7476 - accuracy: 0.1897
40/40 [==============================] - 1s 23ms/step - loss: 3.7476 - accuracy: 0.1897 - val_loss: 3.6220 - val_accuracy: 0.3350
Epoch 2/100
1/40 [..............................] - ETA: 0s - loss: 3.6289 - accuracy: 0.3050
10/40 [======>.......................] - ETA: 0s - loss: 3.5933 - accuracy: 0.3170
19/40 [=============>................] - ETA: 0s - loss: 3.5401 - accuracy: 0.3426
29/40 [====================>.........] - ETA: 0s - loss: 3.4850 - accuracy: 0.3476
37/40 [==========================>...] - ETA: 0s - loss: 3.4371 - accuracy: 0.3564
40/40 [==============================] - 0s 6ms/step - loss: 3.4197 - accuracy: 0.3578
40/40 [==============================] - 0s 10ms/step - loss: 3.4197 - accuracy: 0.3578 - val_loss: 3.1776 - val_accuracy: 0.3960
Epoch 3/100
1/40 [..............................] - ETA: 0s - loss: 3.1771 - accuracy: 0.4050
10/40 [======>.......................] - ETA: 0s - loss: 3.1094 - accuracy: 0.4020
19/40 [=============>................] - ETA: 0s - loss: 3.0591 - accuracy: 0.4089
28/40 [====================>.........] - ETA: 0s - loss: 2.9988 - accuracy: 0.4216
37/40 [==========================>...] - ETA: 0s - loss: 2.9241 - accuracy: 0.4372
40/40 [==============================] - 0s 6ms/step - loss: 2.9025 - accuracy: 0.4445
40/40 [==============================] - 0s 10ms/step - loss: 2.9025 - accuracy: 0.4445 - val_loss: 2.6307 - val_accuracy: 0.5070
Epoch 4/100
1/40 [..............................] - ETA: 0s - loss: 2.5564 - accuracy: 0.4900
10/40 [======>.......................] - ETA: 0s - loss: 2.5309 - accuracy: 0.5200
19/40 [=============>................] - ETA: 0s - loss: 2.4871 - accuracy: 0.5232
28/40 [====================>.........] - ETA: 0s - loss: 2.4367 - accuracy: 0.5268
38/40 [===========================>..] - ETA: 0s - loss: 2.3765 - accuracy: 0.5322
40/40 [==============================] - 0s 6ms/step - loss: 2.3584 - accuracy: 0.5355
40/40 [==============================] - 0s 10ms/step - loss: 2.3584 - accuracy: 0.5355 - val_loss: 2.1442 - val_accuracy: 0.5460
Epoch 5/100
1/40 [..............................] - ETA: 0s - loss: 2.0950 - accuracy: 0.5450
10/40 [======>.......................] - ETA: 0s - loss: 2.0810 - accuracy: 0.5610
19/40 [=============>................] - ETA: 0s - loss: 2.0434 - accuracy: 0.5674
28/40 [====================>.........] - ETA: 0s - loss: 1.9768 - accuracy: 0.5779
37/40 [==========================>...] - ETA: 0s - loss: 1.9596 - accuracy: 0.5759
40/40 [==============================] - 0s 6ms/step - loss: 1.9442 - accuracy: 0.5791
40/40 [==============================] - 0s 10ms/step - loss: 1.9442 - accuracy: 0.5791 - val_loss: 1.8411 - val_accuracy: 0.5820
Epoch 6/100
1/40 [..............................] - ETA: 0s - loss: 1.6941 - accuracy: 0.6150
10/40 [======>.......................] - ETA: 0s - loss: 1.6942 - accuracy: 0.6305
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28/40 [====================>.........] - ETA: 0s - loss: 1.7104 - accuracy: 0.6248
37/40 [==========================>...] - ETA: 0s - loss: 1.6842 - accuracy: 0.6327
40/40 [==============================] - 0s 6ms/step - loss: 1.6775 - accuracy: 0.6338
40/40 [==============================] - 0s 10ms/step - loss: 1.6775 - accuracy: 0.6338 - val_loss: 1.6474 - val_accuracy: 0.6280
Epoch 7/100
1/40 [..............................] - ETA: 0s - loss: 1.8337 - accuracy: 0.5950
10/40 [======>.......................] - ETA: 0s - loss: 1.5574 - accuracy: 0.6650
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29/40 [====================>.........] - ETA: 0s - loss: 1.4892 - accuracy: 0.6798
39/40 [============================>.] - ETA: 0s - loss: 1.4941 - accuracy: 0.6781
40/40 [==============================] - 0s 5ms/step - loss: 1.4889 - accuracy: 0.6794
40/40 [==============================] - 0s 9ms/step - loss: 1.4889 - accuracy: 0.6794 - val_loss: 1.5172 - val_accuracy: 0.6570
Epoch 8/100
1/40 [..............................] - ETA: 0s - loss: 1.5425 - accuracy: 0.6500
11/40 [=======>......................] - ETA: 0s - loss: 1.4041 - accuracy: 0.6955
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39/40 [============================>.] - ETA: 0s - loss: 1.3570 - accuracy: 0.7092
40/40 [==============================] - 0s 5ms/step - loss: 1.3526 - accuracy: 0.7103
40/40 [==============================] - 0s 9ms/step - loss: 1.3526 - accuracy: 0.7103 - val_loss: 1.4247 - val_accuracy: 0.6870
Epoch 9/100
1/40 [..............................] - ETA: 0s - loss: 1.4364 - accuracy: 0.6500
11/40 [=======>......................] - ETA: 0s - loss: 1.2546 - accuracy: 0.7282
20/40 [==============>...............] - ETA: 0s - loss: 1.2599 - accuracy: 0.7230
29/40 [====================>.........] - ETA: 0s - loss: 1.2550 - accuracy: 0.7250
38/40 [===========================>..] - ETA: 0s - loss: 1.2509 - accuracy: 0.7276
40/40 [==============================] - 0s 5ms/step - loss: 1.2476 - accuracy: 0.7286
40/40 [==============================] - 0s 10ms/step - loss: 1.2476 - accuracy: 0.7286 - val_loss: 1.3534 - val_accuracy: 0.7090
Epoch 10/100
1/40 [..............................] - ETA: 0s - loss: 1.2685 - accuracy: 0.7050
10/40 [======>.......................] - ETA: 0s - loss: 1.2191 - accuracy: 0.7380
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28/40 [====================>.........] - ETA: 0s - loss: 1.1724 - accuracy: 0.7461
37/40 [==========================>...] - ETA: 0s - loss: 1.1604 - accuracy: 0.7497
40/40 [==============================] - 0s 6ms/step - loss: 1.1622 - accuracy: 0.7498
40/40 [==============================] - 0s 10ms/step - loss: 1.1622 - accuracy: 0.7498 - val_loss: 1.2994 - val_accuracy: 0.7180
Epoch 11/100
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10/40 [======>.......................] - ETA: 0s - loss: 1.1074 - accuracy: 0.7680
19/40 [=============>................] - ETA: 0s - loss: 1.1159 - accuracy: 0.7626
28/40 [====================>.........] - ETA: 0s - loss: 1.1106 - accuracy: 0.7625
37/40 [==========================>...] - ETA: 0s - loss: 1.0889 - accuracy: 0.7650
40/40 [==============================] - 0s 6ms/step - loss: 1.0872 - accuracy: 0.7674
40/40 [==============================] - 0s 10ms/step - loss: 1.0872 - accuracy: 0.7674 - val_loss: 1.2548 - val_accuracy: 0.7230
Epoch 12/100
1/40 [..............................] - ETA: 0s - loss: 0.8476 - accuracy: 0.8250
10/40 [======>.......................] - ETA: 0s - loss: 1.0671 - accuracy: 0.7790
19/40 [=============>................] - ETA: 0s - loss: 1.0574 - accuracy: 0.7747
28/40 [====================>.........] - ETA: 0s - loss: 1.0271 - accuracy: 0.7816
37/40 [==========================>...] - ETA: 0s - loss: 1.0256 - accuracy: 0.7809
40/40 [==============================] - 0s 6ms/step - loss: 1.0213 - accuracy: 0.7820
40/40 [==============================] - 0s 10ms/step - loss: 1.0213 - accuracy: 0.7820 - val_loss: 1.2177 - val_accuracy: 0.7360
Epoch 13/100
1/40 [..............................] - ETA: 0s - loss: 0.9642 - accuracy: 0.8000
10/40 [======>.......................] - ETA: 0s - loss: 1.0070 - accuracy: 0.7885
19/40 [=============>................] - ETA: 0s - loss: 0.9927 - accuracy: 0.7905
27/40 [===================>..........] - ETA: 0s - loss: 0.9784 - accuracy: 0.7880
36/40 [==========================>...] - ETA: 0s - loss: 0.9642 - accuracy: 0.7922
40/40 [==============================] - 0s 6ms/step - loss: 0.9601 - accuracy: 0.7930
40/40 [==============================] - 0s 10ms/step - loss: 0.9601 - accuracy: 0.7930 - val_loss: 1.1822 - val_accuracy: 0.7450
Epoch 14/100
1/40 [..............................] - ETA: 0s - loss: 0.9541 - accuracy: 0.8000
10/40 [======>.......................] - ETA: 0s - loss: 0.9489 - accuracy: 0.7970
19/40 [=============>................] - ETA: 0s - loss: 0.9211 - accuracy: 0.8026
28/40 [====================>.........] - ETA: 0s - loss: 0.9093 - accuracy: 0.8037
37/40 [==========================>...] - ETA: 0s - loss: 0.9017 - accuracy: 0.8055
40/40 [==============================] - 0s 6ms/step - loss: 0.9031 - accuracy: 0.8062
40/40 [==============================] - 0s 10ms/step - loss: 0.9031 - accuracy: 0.8062 - val_loss: 1.1530 - val_accuracy: 0.7520
Epoch 15/100
1/40 [..............................] - ETA: 0s - loss: 0.6530 - accuracy: 0.8650
10/40 [======>.......................] - ETA: 0s - loss: 0.8356 - accuracy: 0.8235
19/40 [=============>................] - ETA: 0s - loss: 0.8492 - accuracy: 0.8200
28/40 [====================>.........] - ETA: 0s - loss: 0.8616 - accuracy: 0.8146
37/40 [==========================>...] - ETA: 0s - loss: 0.8524 - accuracy: 0.8153
40/40 [==============================] - 0s 6ms/step - loss: 0.8506 - accuracy: 0.8167
40/40 [==============================] - 0s 10ms/step - loss: 0.8506 - accuracy: 0.8167 - val_loss: 1.1282 - val_accuracy: 0.7560
Epoch 16/100
1/40 [..............................] - ETA: 0s - loss: 0.7470 - accuracy: 0.8350
10/40 [======>.......................] - ETA: 0s - loss: 0.7852 - accuracy: 0.8345
19/40 [=============>................] - ETA: 0s - loss: 0.7892 - accuracy: 0.8266
28/40 [====================>.........] - ETA: 0s - loss: 0.8042 - accuracy: 0.8232
37/40 [==========================>...] - ETA: 0s - loss: 0.7930 - accuracy: 0.8261
40/40 [==============================] - 0s 6ms/step - loss: 0.7992 - accuracy: 0.8259
40/40 [==============================] - 0s 10ms/step - loss: 0.7992 - accuracy: 0.8259 - val_loss: 1.1038 - val_accuracy: 0.7620
Epoch 17/100
1/40 [..............................] - ETA: 0s - loss: 0.7903 - accuracy: 0.8400
10/40 [======>.......................] - ETA: 0s - loss: 0.7812 - accuracy: 0.8300
19/40 [=============>................] - ETA: 0s - loss: 0.7650 - accuracy: 0.8345
28/40 [====================>.........] - ETA: 0s - loss: 0.7616 - accuracy: 0.8323
37/40 [==========================>...] - ETA: 0s - loss: 0.7539 - accuracy: 0.8341
40/40 [==============================] - 0s 6ms/step - loss: 0.7519 - accuracy: 0.8339
40/40 [==============================] - 0s 10ms/step - loss: 0.7519 - accuracy: 0.8339 - val_loss: 1.0870 - val_accuracy: 0.7640
Epoch 18/100
1/40 [..............................] - ETA: 0s - loss: 0.7554 - accuracy: 0.8400
10/40 [======>.......................] - ETA: 0s - loss: 0.7012 - accuracy: 0.8450
19/40 [=============>................] - ETA: 0s - loss: 0.7026 - accuracy: 0.8442
28/40 [====================>.........] - ETA: 0s - loss: 0.7079 - accuracy: 0.8427
37/40 [==========================>...] - ETA: 0s - loss: 0.7097 - accuracy: 0.8423
40/40 [==============================] - 0s 6ms/step - loss: 0.7070 - accuracy: 0.8429
40/40 [==============================] - 0s 10ms/step - loss: 0.7070 - accuracy: 0.8429 - val_loss: 1.0658 - val_accuracy: 0.7680
Epoch 19/100
1/40 [..............................] - ETA: 0s - loss: 0.7264 - accuracy: 0.8500
10/40 [======>.......................] - ETA: 0s - loss: 0.6717 - accuracy: 0.8495
18/40 [============>.................] - ETA: 0s - loss: 0.6644 - accuracy: 0.8531
27/40 [===================>..........] - ETA: 0s - loss: 0.6740 - accuracy: 0.8526
36/40 [==========================>...] - ETA: 0s - loss: 0.6667 - accuracy: 0.8529
40/40 [==============================] - 0s 6ms/step - loss: 0.6653 - accuracy: 0.8529
40/40 [==============================] - 0s 10ms/step - loss: 0.6653 - accuracy: 0.8529 - val_loss: 1.0487 - val_accuracy: 0.7700
Epoch 20/100
1/40 [..............................] - ETA: 0s - loss: 0.5781 - accuracy: 0.8950
10/40 [======>.......................] - ETA: 0s - loss: 0.6543 - accuracy: 0.8590
19/40 [=============>................] - ETA: 0s - loss: 0.6327 - accuracy: 0.8605
28/40 [====================>.........] - ETA: 0s - loss: 0.6263 - accuracy: 0.8600
37/40 [==========================>...] - ETA: 0s - loss: 0.6244 - accuracy: 0.8612
40/40 [==============================] - 0s 6ms/step - loss: 0.6250 - accuracy: 0.8627
40/40 [==============================] - 0s 10ms/step - loss: 0.6250 - accuracy: 0.8627 - val_loss: 1.0350 - val_accuracy: 0.7770
Epoch 21/100
1/40 [..............................] - ETA: 0s - loss: 0.6024 - accuracy: 0.8850
10/40 [======>.......................] - ETA: 0s - loss: 0.5726 - accuracy: 0.8740
19/40 [=============>................] - ETA: 0s - loss: 0.5564 - accuracy: 0.8768
28/40 [====================>.........] - ETA: 0s - loss: 0.5748 - accuracy: 0.8743
37/40 [==========================>...] - ETA: 0s - loss: 0.5800 - accuracy: 0.8714
40/40 [==============================] - 0s 6ms/step - loss: 0.5868 - accuracy: 0.8701
40/40 [==============================] - 0s 10ms/step - loss: 0.5868 - accuracy: 0.8701 - val_loss: 1.0236 - val_accuracy: 0.7780
Epoch 22/100
1/40 [..............................] - ETA: 0s - loss: 0.5907 - accuracy: 0.8800
10/40 [======>.......................] - ETA: 0s - loss: 0.5751 - accuracy: 0.8730
19/40 [=============>................] - ETA: 0s - loss: 0.5759 - accuracy: 0.8724
28/40 [====================>.........] - ETA: 0s - loss: 0.5700 - accuracy: 0.8757
38/40 [===========================>..] - ETA: 0s - loss: 0.5530 - accuracy: 0.8793
40/40 [==============================] - 0s 6ms/step - loss: 0.5517 - accuracy: 0.8794
40/40 [==============================] - 0s 10ms/step - loss: 0.5517 - accuracy: 0.8794 - val_loss: 1.0114 - val_accuracy: 0.7810
Epoch 23/100
1/40 [..............................] - ETA: 0s - loss: 0.6911 - accuracy: 0.8650
10/40 [======>.......................] - ETA: 0s - loss: 0.5672 - accuracy: 0.8845
20/40 [==============>...............] - ETA: 0s - loss: 0.5163 - accuracy: 0.8903
29/40 [====================>.........] - ETA: 0s - loss: 0.5090 - accuracy: 0.8900
38/40 [===========================>..] - ETA: 0s - loss: 0.5200 - accuracy: 0.8863
40/40 [==============================] - 0s 6ms/step - loss: 0.5178 - accuracy: 0.8865
40/40 [==============================] - 0s 10ms/step - loss: 0.5178 - accuracy: 0.8865 - val_loss: 0.9992 - val_accuracy: 0.7890
Epoch 24/100
1/40 [..............................] - ETA: 0s - loss: 0.4928 - accuracy: 0.9000
10/40 [======>.......................] - ETA: 0s - loss: 0.4911 - accuracy: 0.8915
19/40 [=============>................] - ETA: 0s - loss: 0.4874 - accuracy: 0.8932
28/40 [====================>.........] - ETA: 0s - loss: 0.4781 - accuracy: 0.8959
37/40 [==========================>...] - ETA: 0s - loss: 0.4835 - accuracy: 0.8953
40/40 [==============================] - 0s 6ms/step - loss: 0.4868 - accuracy: 0.8941
40/40 [==============================] - 0s 10ms/step - loss: 0.4868 - accuracy: 0.8941 - val_loss: 0.9911 - val_accuracy: 0.7890
Epoch 25/100
1/40 [..............................] - ETA: 0s - loss: 0.4697 - accuracy: 0.9100
10/40 [======>.......................] - ETA: 0s - loss: 0.4831 - accuracy: 0.8925
19/40 [=============>................] - ETA: 0s - loss: 0.4727 - accuracy: 0.9003
28/40 [====================>.........] - ETA: 0s - loss: 0.4633 - accuracy: 0.9009
37/40 [==========================>...] - ETA: 0s - loss: 0.4565 - accuracy: 0.9026
40/40 [==============================] - 0s 6ms/step - loss: 0.4572 - accuracy: 0.9015
40/40 [==============================] - 0s 10ms/step - loss: 0.4572 - accuracy: 0.9015 - val_loss: 0.9843 - val_accuracy: 0.7910
Epoch 26/100
1/40 [..............................] - ETA: 0s - loss: 0.2755 - accuracy: 0.9600
11/40 [=======>......................] - ETA: 0s - loss: 0.4148 - accuracy: 0.9155
20/40 [==============>...............] - ETA: 0s - loss: 0.4247 - accuracy: 0.9110
29/40 [====================>.........] - ETA: 0s - loss: 0.4328 - accuracy: 0.9091
38/40 [===========================>..] - ETA: 0s - loss: 0.4327 - accuracy: 0.9093
40/40 [==============================] - 0s 6ms/step - loss: 0.4289 - accuracy: 0.9098
40/40 [==============================] - 0s 9ms/step - loss: 0.4289 - accuracy: 0.9098 - val_loss: 0.9791 - val_accuracy: 0.7920
Epoch 27/100
1/40 [..............................] - ETA: 0s - loss: 0.4811 - accuracy: 0.9150
10/40 [======>.......................] - ETA: 0s - loss: 0.3968 - accuracy: 0.9215
19/40 [=============>................] - ETA: 0s - loss: 0.3908 - accuracy: 0.9161
28/40 [====================>.........] - ETA: 0s - loss: 0.3930 - accuracy: 0.9146
37/40 [==========================>...] - ETA: 0s - loss: 0.4028 - accuracy: 0.9120
40/40 [==============================] - 0s 6ms/step - loss: 0.4030 - accuracy: 0.9131
40/40 [==============================] - 0s 10ms/step - loss: 0.4030 - accuracy: 0.9131 - val_loss: 0.9754 - val_accuracy: 0.7900
Epoch 28/100
1/40 [..............................] - ETA: 0s - loss: 0.4768 - accuracy: 0.8800
10/40 [======>.......................] - ETA: 0s - loss: 0.3947 - accuracy: 0.9145
19/40 [=============>................] - ETA: 0s - loss: 0.3983 - accuracy: 0.9166
28/40 [====================>.........] - ETA: 0s - loss: 0.3885 - accuracy: 0.9175
37/40 [==========================>...] - ETA: 0s - loss: 0.3776 - accuracy: 0.9193
40/40 [==============================] - 0s 6ms/step - loss: 0.3785 - accuracy: 0.9196
40/40 [==============================] - 0s 10ms/step - loss: 0.3785 - accuracy: 0.9196 - val_loss: 0.9686 - val_accuracy: 0.7940
Epoch 29/100
1/40 [..............................] - ETA: 0s - loss: 0.4786 - accuracy: 0.8900
10/40 [======>.......................] - ETA: 0s - loss: 0.3472 - accuracy: 0.9290
19/40 [=============>................] - ETA: 0s - loss: 0.3382 - accuracy: 0.9313
28/40 [====================>.........] - ETA: 0s - loss: 0.3495 - accuracy: 0.9264
37/40 [==========================>...] - ETA: 0s - loss: 0.3545 - accuracy: 0.9253
40/40 [==============================] - 0s 6ms/step - loss: 0.3562 - accuracy: 0.9247
40/40 [==============================] - 0s 9ms/step - loss: 0.3562 - accuracy: 0.9247 - val_loss: 0.9663 - val_accuracy: 0.7950
Epoch 30/100
1/40 [..............................] - ETA: 0s - loss: 0.3393 - accuracy: 0.9200
10/40 [======>.......................] - ETA: 0s - loss: 0.3128 - accuracy: 0.9285
19/40 [=============>................] - ETA: 0s - loss: 0.3216 - accuracy: 0.9261
28/40 [====================>.........] - ETA: 0s - loss: 0.3322 - accuracy: 0.9271
37/40 [==========================>...] - ETA: 0s - loss: 0.3334 - accuracy: 0.9276
40/40 [==============================] - 0s 6ms/step - loss: 0.3354 - accuracy: 0.9272
40/40 [==============================] - 0s 10ms/step - loss: 0.3354 - accuracy: 0.9272 - val_loss: 0.9617 - val_accuracy: 0.7970
Epoch 31/100
1/40 [..............................] - ETA: 0s - loss: 0.2674 - accuracy: 0.9400
10/40 [======>.......................] - ETA: 0s - loss: 0.3211 - accuracy: 0.9275
19/40 [=============>................] - ETA: 0s - loss: 0.3064 - accuracy: 0.9337
28/40 [====================>.........] - ETA: 0s - loss: 0.3140 - accuracy: 0.9320
37/40 [==========================>...] - ETA: 0s - loss: 0.3170 - accuracy: 0.9308
40/40 [==============================] - 0s 6ms/step - loss: 0.3168 - accuracy: 0.9308
40/40 [==============================] - 0s 10ms/step - loss: 0.3168 - accuracy: 0.9308 - val_loss: 0.9645 - val_accuracy: 0.7910
Epoch 32/100
1/40 [..............................] - ETA: 0s - loss: 0.2520 - accuracy: 0.9600
10/40 [======>.......................] - ETA: 0s - loss: 0.3030 - accuracy: 0.9395
19/40 [=============>................] - ETA: 0s - loss: 0.2988 - accuracy: 0.9368
28/40 [====================>.........] - ETA: 0s - loss: 0.2998 - accuracy: 0.9373
37/40 [==========================>...] - ETA: 0s - loss: 0.2973 - accuracy: 0.9357
40/40 [==============================] - 0s 6ms/step - loss: 0.2983 - accuracy: 0.9345
40/40 [==============================] - 0s 10ms/step - loss: 0.2983 - accuracy: 0.9345 - val_loss: 0.9622 - val_accuracy: 0.8010
Epoch 33/100
1/40 [..............................] - ETA: 0s - loss: 0.2407 - accuracy: 0.9400
10/40 [======>.......................] - ETA: 0s - loss: 0.2872 - accuracy: 0.9400
19/40 [=============>................] - ETA: 0s - loss: 0.2846 - accuracy: 0.9395
28/40 [====================>.........] - ETA: 0s - loss: 0.2839 - accuracy: 0.9395
37/40 [==========================>...] - ETA: 0s - loss: 0.2817 - accuracy: 0.9384
40/40 [==============================] - 0s 6ms/step - loss: 0.2816 - accuracy: 0.9382
40/40 [==============================] - 0s 9ms/step - loss: 0.2816 - accuracy: 0.9382 - val_loss: 0.9724 - val_accuracy: 0.7980
Epoch 34/100
1/40 [..............................] - ETA: 0s - loss: 0.2366 - accuracy: 0.9450
10/40 [======>.......................] - ETA: 0s - loss: 0.2526 - accuracy: 0.9515
19/40 [=============>................] - ETA: 0s - loss: 0.2678 - accuracy: 0.9413
28/40 [====================>.........] - ETA: 0s - loss: 0.2740 - accuracy: 0.9398
37/40 [==========================>...] - ETA: 0s - loss: 0.2680 - accuracy: 0.9409
40/40 [==============================] - 0s 6ms/step - loss: 0.2684 - accuracy: 0.9410
40/40 [==============================] - 0s 9ms/step - loss: 0.2684 - accuracy: 0.9410 - val_loss: 0.9682 - val_accuracy: 0.7930
Epoch 35/100
1/40 [..............................] - ETA: 0s - loss: 0.2197 - accuracy: 0.9600
10/40 [======>.......................] - ETA: 0s - loss: 0.2277 - accuracy: 0.9560
19/40 [=============>................] - ETA: 0s - loss: 0.2445 - accuracy: 0.9484
28/40 [====================>.........] - ETA: 0s - loss: 0.2525 - accuracy: 0.9438
37/40 [==========================>...] - ETA: 0s - loss: 0.2502 - accuracy: 0.9430
40/40 [==============================] - 0s 6ms/step - loss: 0.2524 - accuracy: 0.9421
40/40 [==============================] - 0s 10ms/step - loss: 0.2524 - accuracy: 0.9421 - val_loss: 0.9726 - val_accuracy: 0.7970
Epoch 36/100
1/40 [..............................] - ETA: 0s - loss: 0.2761 - accuracy: 0.9250
10/40 [======>.......................] - ETA: 0s - loss: 0.2457 - accuracy: 0.9450
19/40 [=============>................] - ETA: 0s - loss: 0.2278 - accuracy: 0.9495
29/40 [====================>.........] - ETA: 0s - loss: 0.2366 - accuracy: 0.9474
38/40 [===========================>..] - ETA: 0s - loss: 0.2395 - accuracy: 0.9458
40/40 [==============================] - 0s 6ms/step - loss: 0.2395 - accuracy: 0.9456
40/40 [==============================] - 0s 9ms/step - loss: 0.2395 - accuracy: 0.9456 - val_loss: 0.9711 - val_accuracy: 0.8010
Epoch 37/100
1/40 [..............................] - ETA: 0s - loss: 0.1749 - accuracy: 0.9750
10/40 [======>.......................] - ETA: 0s - loss: 0.2298 - accuracy: 0.9475
19/40 [=============>................] - ETA: 0s - loss: 0.2261 - accuracy: 0.9492
28/40 [====================>.........] - ETA: 0s - loss: 0.2275 - accuracy: 0.9488
37/40 [==========================>...] - ETA: 0s - loss: 0.2240 - accuracy: 0.9476
40/40 [==============================] - 0s 6ms/step - loss: 0.2266 - accuracy: 0.9460
40/40 [==============================] - 0s 10ms/step - loss: 0.2266 - accuracy: 0.9460 - val_loss: 0.9757 - val_accuracy: 0.8020
Epoch 38/100
1/40 [..............................] - ETA: 0s - loss: 0.2235 - accuracy: 0.9350
10/40 [======>.......................] - ETA: 0s - loss: 0.2173 - accuracy: 0.9490
19/40 [=============>................] - ETA: 0s - loss: 0.2205 - accuracy: 0.9466
28/40 [====================>.........] - ETA: 0s - loss: 0.2178 - accuracy: 0.9475
37/40 [==========================>...] - ETA: 0s - loss: 0.2163 - accuracy: 0.9470
40/40 [==============================] - 0s 6ms/step - loss: 0.2164 - accuracy: 0.9473
40/40 [==============================] - 0s 10ms/step - loss: 0.2164 - accuracy: 0.9473 - val_loss: 0.9807 - val_accuracy: 0.8010
Epoch 39/100
1/40 [..............................] - ETA: 0s - loss: 0.2093 - accuracy: 0.9700
10/40 [======>.......................] - ETA: 0s - loss: 0.2018 - accuracy: 0.9570
19/40 [=============>................] - ETA: 0s - loss: 0.2085 - accuracy: 0.9547
28/40 [====================>.........] - ETA: 0s - loss: 0.2122 - accuracy: 0.9505
37/40 [==========================>...] - ETA: 0s - loss: 0.2081 - accuracy: 0.9485
40/40 [==============================] - 0s 6ms/step - loss: 0.2068 - accuracy: 0.9488
40/40 [==============================] - 0s 10ms/step - loss: 0.2068 - accuracy: 0.9488 - val_loss: 0.9833 - val_accuracy: 0.8020
Epoch 40/100
1/40 [..............................] - ETA: 0s - loss: 0.2252 - accuracy: 0.9500
10/40 [======>.......................] - ETA: 0s - loss: 0.1975 - accuracy: 0.9570
19/40 [=============>................] - ETA: 0s - loss: 0.1853 - accuracy: 0.9592
28/40 [====================>.........] - ETA: 0s - loss: 0.1940 - accuracy: 0.9543
37/40 [==========================>...] - ETA: 0s - loss: 0.1982 - accuracy: 0.9515
40/40 [==============================] - 0s 6ms/step - loss: 0.1980 - accuracy: 0.9511
40/40 [==============================] - 0s 10ms/step - loss: 0.1980 - accuracy: 0.9511 - val_loss: 0.9946 - val_accuracy: 0.8060
Epoch 41/100
1/40 [..............................] - ETA: 0s - loss: 0.2139 - accuracy: 0.9550
10/40 [======>.......................] - ETA: 0s - loss: 0.1894 - accuracy: 0.9570
19/40 [=============>................] - ETA: 0s - loss: 0.1869 - accuracy: 0.9537
27/40 [===================>..........] - ETA: 0s - loss: 0.1900 - accuracy: 0.9526
36/40 [==========================>...] - ETA: 0s - loss: 0.1883 - accuracy: 0.9510
40/40 [==============================] - 0s 6ms/step - loss: 0.1897 - accuracy: 0.9513
40/40 [==============================] - 0s 10ms/step - loss: 0.1897 - accuracy: 0.9513 - val_loss: 0.9988 - val_accuracy: 0.7990
Epoch 42/100
1/40 [..............................] - ETA: 0s - loss: 0.1965 - accuracy: 0.9400
10/40 [======>.......................] - ETA: 0s - loss: 0.1700 - accuracy: 0.9595
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28/40 [====================>.........] - ETA: 0s - loss: 0.1760 - accuracy: 0.9570
37/40 [==========================>...] - ETA: 0s - loss: 0.1809 - accuracy: 0.9535
40/40 [==============================] - 0s 6ms/step - loss: 0.1833 - accuracy: 0.9511
40/40 [==============================] - 0s 10ms/step - loss: 0.1833 - accuracy: 0.9511 - val_loss: 0.9997 - val_accuracy: 0.8040
Epoch 43/100
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40/40 [==============================] - 0s 5ms/step - loss: 0.1749 - accuracy: 0.9520
40/40 [==============================] - 0s 9ms/step - loss: 0.1749 - accuracy: 0.9520 - val_loss: 0.9985 - val_accuracy: 0.8060
Epoch 44/100
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11/40 [=======>......................] - ETA: 0s - loss: 0.1739 - accuracy: 0.9555
21/40 [==============>...............] - ETA: 0s - loss: 0.1641 - accuracy: 0.9564
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40/40 [==============================] - 0s 5ms/step - loss: 0.1684 - accuracy: 0.9534
40/40 [==============================] - 0s 9ms/step - loss: 0.1684 - accuracy: 0.9534 - val_loss: 1.0111 - val_accuracy: 0.8050
Epoch 45/100
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30/40 [=====================>........] - ETA: 0s - loss: 0.1616 - accuracy: 0.9550
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40/40 [==============================] - 0s 6ms/step - loss: 0.1620 - accuracy: 0.9543
40/40 [==============================] - 0s 9ms/step - loss: 0.1620 - accuracy: 0.9543 - val_loss: 1.0049 - val_accuracy: 0.8050
Epoch 46/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.1567 - accuracy: 0.9546
40/40 [==============================] - 0s 9ms/step - loss: 0.1567 - accuracy: 0.9546 - val_loss: 1.0102 - val_accuracy: 0.8090
Epoch 47/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.1504 - accuracy: 0.9558
40/40 [==============================] - 0s 10ms/step - loss: 0.1504 - accuracy: 0.9558 - val_loss: 1.0145 - val_accuracy: 0.8090
Epoch 48/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.1471 - accuracy: 0.9559
40/40 [==============================] - 0s 9ms/step - loss: 0.1471 - accuracy: 0.9559 - val_loss: 1.0227 - val_accuracy: 0.8090
Epoch 49/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.1411 - accuracy: 0.9562
40/40 [==============================] - 0s 10ms/step - loss: 0.1411 - accuracy: 0.9562 - val_loss: 1.0320 - val_accuracy: 0.8050
Epoch 50/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.1371 - accuracy: 0.9564
40/40 [==============================] - 0s 10ms/step - loss: 0.1371 - accuracy: 0.9564 - val_loss: 1.0372 - val_accuracy: 0.8060
Epoch 51/100
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36/40 [==========================>...] - ETA: 0s - loss: 0.1279 - accuracy: 0.9589
40/40 [==============================] - 0s 6ms/step - loss: 0.1357 - accuracy: 0.9564
40/40 [==============================] - 0s 10ms/step - loss: 0.1357 - accuracy: 0.9564 - val_loss: 1.0360 - val_accuracy: 0.8060
Epoch 52/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1265 - accuracy: 0.9595
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40/40 [==============================] - 0s 6ms/step - loss: 0.1294 - accuracy: 0.9574
40/40 [==============================] - 0s 9ms/step - loss: 0.1294 - accuracy: 0.9574 - val_loss: 1.0365 - val_accuracy: 0.8130
Epoch 53/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1196 - accuracy: 0.9690
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40/40 [==============================] - 0s 6ms/step - loss: 0.1261 - accuracy: 0.9600
40/40 [==============================] - 0s 10ms/step - loss: 0.1261 - accuracy: 0.9600 - val_loss: 1.0408 - val_accuracy: 0.8090
Epoch 54/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.1179 - accuracy: 0.9609
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40/40 [==============================] - 0s 6ms/step - loss: 0.1220 - accuracy: 0.9587
40/40 [==============================] - 0s 10ms/step - loss: 0.1220 - accuracy: 0.9587 - val_loss: 1.0511 - val_accuracy: 0.8090
Epoch 55/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1201 - accuracy: 0.9620
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28/40 [====================>.........] - ETA: 0s - loss: 0.1164 - accuracy: 0.9621
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40/40 [==============================] - 0s 6ms/step - loss: 0.1194 - accuracy: 0.9592
40/40 [==============================] - 0s 10ms/step - loss: 0.1194 - accuracy: 0.9592 - val_loss: 1.0564 - val_accuracy: 0.8090
Epoch 56/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1050 - accuracy: 0.9670
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29/40 [====================>.........] - ETA: 0s - loss: 0.1168 - accuracy: 0.9628
38/40 [===========================>..] - ETA: 0s - loss: 0.1175 - accuracy: 0.9607
40/40 [==============================] - 0s 5ms/step - loss: 0.1177 - accuracy: 0.9598
40/40 [==============================] - 0s 9ms/step - loss: 0.1177 - accuracy: 0.9598 - val_loss: 1.0605 - val_accuracy: 0.8090
Epoch 57/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1030 - accuracy: 0.9705
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28/40 [====================>.........] - ETA: 0s - loss: 0.1135 - accuracy: 0.9645
37/40 [==========================>...] - ETA: 0s - loss: 0.1139 - accuracy: 0.9627
40/40 [==============================] - 0s 6ms/step - loss: 0.1161 - accuracy: 0.9620
40/40 [==============================] - 0s 10ms/step - loss: 0.1161 - accuracy: 0.9620 - val_loss: 1.0650 - val_accuracy: 0.8070
Epoch 58/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1070 - accuracy: 0.9650
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28/40 [====================>.........] - ETA: 0s - loss: 0.1086 - accuracy: 0.9655
37/40 [==========================>...] - ETA: 0s - loss: 0.1138 - accuracy: 0.9628
40/40 [==============================] - 0s 6ms/step - loss: 0.1134 - accuracy: 0.9619
40/40 [==============================] - 0s 10ms/step - loss: 0.1134 - accuracy: 0.9619 - val_loss: 1.0627 - val_accuracy: 0.8090
Epoch 59/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.0978 - accuracy: 0.9675
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28/40 [====================>.........] - ETA: 0s - loss: 0.1078 - accuracy: 0.9639
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40/40 [==============================] - 0s 6ms/step - loss: 0.1091 - accuracy: 0.9610
40/40 [==============================] - 0s 10ms/step - loss: 0.1091 - accuracy: 0.9610 - val_loss: 1.0721 - val_accuracy: 0.8040
Epoch 60/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1057 - accuracy: 0.9685
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38/40 [===========================>..] - ETA: 0s - loss: 0.1076 - accuracy: 0.9608
40/40 [==============================] - 0s 6ms/step - loss: 0.1076 - accuracy: 0.9604
40/40 [==============================] - 0s 10ms/step - loss: 0.1076 - accuracy: 0.9604 - val_loss: 1.0755 - val_accuracy: 0.8090
Epoch 61/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.1043 - accuracy: 0.9665
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28/40 [====================>.........] - ETA: 0s - loss: 0.1024 - accuracy: 0.9641
37/40 [==========================>...] - ETA: 0s - loss: 0.1051 - accuracy: 0.9614
40/40 [==============================] - 0s 6ms/step - loss: 0.1059 - accuracy: 0.9604
40/40 [==============================] - 0s 10ms/step - loss: 0.1059 - accuracy: 0.9604 - val_loss: 1.0814 - val_accuracy: 0.8070
Epoch 62/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.0890 - accuracy: 0.9690
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29/40 [====================>.........] - ETA: 0s - loss: 0.0991 - accuracy: 0.9650
38/40 [===========================>..] - ETA: 0s - loss: 0.1012 - accuracy: 0.9622
40/40 [==============================] - 0s 6ms/step - loss: 0.1028 - accuracy: 0.9612
40/40 [==============================] - 0s 10ms/step - loss: 0.1028 - accuracy: 0.9612 - val_loss: 1.0996 - val_accuracy: 0.8020
Epoch 63/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.0886 - accuracy: 0.9675
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28/40 [====================>.........] - ETA: 0s - loss: 0.1025 - accuracy: 0.9591
37/40 [==========================>...] - ETA: 0s - loss: 0.1015 - accuracy: 0.9586
40/40 [==============================] - 0s 6ms/step - loss: 0.1018 - accuracy: 0.9589
40/40 [==============================] - 0s 10ms/step - loss: 0.1018 - accuracy: 0.9589 - val_loss: 1.0930 - val_accuracy: 0.8010
Epoch 64/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0985 - accuracy: 0.9643
36/40 [==========================>...] - ETA: 0s - loss: 0.0998 - accuracy: 0.9626
40/40 [==============================] - 0s 6ms/step - loss: 0.1001 - accuracy: 0.9624
40/40 [==============================] - 0s 10ms/step - loss: 0.1001 - accuracy: 0.9624 - val_loss: 1.1019 - val_accuracy: 0.8070
Epoch 65/100
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38/40 [===========================>..] - ETA: 0s - loss: 0.0987 - accuracy: 0.9603
40/40 [==============================] - 0s 6ms/step - loss: 0.0976 - accuracy: 0.9610
40/40 [==============================] - 0s 9ms/step - loss: 0.0976 - accuracy: 0.9610 - val_loss: 1.1069 - val_accuracy: 0.8050
Epoch 66/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0960 - accuracy: 0.9613
40/40 [==============================] - 0s 10ms/step - loss: 0.0960 - accuracy: 0.9613 - val_loss: 1.0986 - val_accuracy: 0.8050
Epoch 67/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0952 - accuracy: 0.9599
40/40 [==============================] - 0s 10ms/step - loss: 0.0952 - accuracy: 0.9599 - val_loss: 1.1073 - val_accuracy: 0.8050
Epoch 68/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0943 - accuracy: 0.9622
40/40 [==============================] - 0s 9ms/step - loss: 0.0943 - accuracy: 0.9622 - val_loss: 1.1151 - val_accuracy: 0.8050
Epoch 69/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0882 - accuracy: 0.9671
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40/40 [==============================] - 0s 6ms/step - loss: 0.0931 - accuracy: 0.9634
40/40 [==============================] - 0s 9ms/step - loss: 0.0931 - accuracy: 0.9634 - val_loss: 1.1147 - val_accuracy: 0.8050
Epoch 70/100
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11/40 [=======>......................] - ETA: 0s - loss: 0.0875 - accuracy: 0.9659
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29/40 [====================>.........] - ETA: 0s - loss: 0.0902 - accuracy: 0.9629
38/40 [===========================>..] - ETA: 0s - loss: 0.0936 - accuracy: 0.9604
40/40 [==============================] - 0s 6ms/step - loss: 0.0937 - accuracy: 0.9604
40/40 [==============================] - 0s 10ms/step - loss: 0.0937 - accuracy: 0.9604 - val_loss: 1.1252 - val_accuracy: 0.8060
Epoch 71/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0873 - accuracy: 0.9659
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40/40 [==============================] - 0s 6ms/step - loss: 0.0901 - accuracy: 0.9633
40/40 [==============================] - 0s 10ms/step - loss: 0.0901 - accuracy: 0.9633 - val_loss: 1.1302 - val_accuracy: 0.8060
Epoch 72/100
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29/40 [====================>.........] - ETA: 0s - loss: 0.0890 - accuracy: 0.9628
38/40 [===========================>..] - ETA: 0s - loss: 0.0886 - accuracy: 0.9618
40/40 [==============================] - 0s 6ms/step - loss: 0.0883 - accuracy: 0.9615
40/40 [==============================] - 0s 9ms/step - loss: 0.0883 - accuracy: 0.9615 - val_loss: 1.1265 - val_accuracy: 0.7990
Epoch 73/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0797 - accuracy: 0.9704
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40/40 [==============================] - 0s 6ms/step - loss: 0.0874 - accuracy: 0.9630
40/40 [==============================] - 0s 10ms/step - loss: 0.0874 - accuracy: 0.9630 - val_loss: 1.1363 - val_accuracy: 0.8030
Epoch 74/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.0793 - accuracy: 0.9720
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40/40 [==============================] - 0s 6ms/step - loss: 0.0874 - accuracy: 0.9632
40/40 [==============================] - 0s 9ms/step - loss: 0.0874 - accuracy: 0.9632 - val_loss: 1.1330 - val_accuracy: 0.8060
Epoch 75/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0840 - accuracy: 0.9664
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40/40 [==============================] - 0s 6ms/step - loss: 0.0872 - accuracy: 0.9635
40/40 [==============================] - 0s 10ms/step - loss: 0.0872 - accuracy: 0.9635 - val_loss: 1.1405 - val_accuracy: 0.8030
Epoch 76/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0807 - accuracy: 0.9659
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40/40 [==============================] - 0s 6ms/step - loss: 0.0855 - accuracy: 0.9625
40/40 [==============================] - 0s 10ms/step - loss: 0.0855 - accuracy: 0.9625 - val_loss: 1.1355 - val_accuracy: 0.8040
Epoch 77/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0845 - accuracy: 0.9624
40/40 [==============================] - 0s 9ms/step - loss: 0.0845 - accuracy: 0.9624 - val_loss: 1.1533 - val_accuracy: 0.8020
Epoch 78/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0844 - accuracy: 0.9628
40/40 [==============================] - 0s 10ms/step - loss: 0.0844 - accuracy: 0.9628 - val_loss: 1.1384 - val_accuracy: 0.8030
Epoch 79/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0841 - accuracy: 0.9625
40/40 [==============================] - 0s 10ms/step - loss: 0.0841 - accuracy: 0.9625 - val_loss: 1.1641 - val_accuracy: 0.8020
Epoch 80/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0836 - accuracy: 0.9625
40/40 [==============================] - 0s 9ms/step - loss: 0.0836 - accuracy: 0.9625 - val_loss: 1.1683 - val_accuracy: 0.8010
Epoch 81/100
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10/40 [======>.......................] - ETA: 0s - loss: 0.0807 - accuracy: 0.9645
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40/40 [==============================] - 0s 6ms/step - loss: 0.0818 - accuracy: 0.9618
40/40 [==============================] - 0s 10ms/step - loss: 0.0818 - accuracy: 0.9618 - val_loss: 1.1752 - val_accuracy: 0.8020
Epoch 82/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0821 - accuracy: 0.9602
40/40 [==============================] - 0s 9ms/step - loss: 0.0821 - accuracy: 0.9602 - val_loss: 1.1707 - val_accuracy: 0.8000
Epoch 83/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0792 - accuracy: 0.9627
40/40 [==============================] - 0s 10ms/step - loss: 0.0792 - accuracy: 0.9627 - val_loss: 1.1732 - val_accuracy: 0.8070
Epoch 84/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0798 - accuracy: 0.9624
40/40 [==============================] - 0s 10ms/step - loss: 0.0798 - accuracy: 0.9624 - val_loss: 1.1669 - val_accuracy: 0.8000
Epoch 85/100
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40/40 [==============================] - 0s 5ms/step - loss: 0.0804 - accuracy: 0.9610
40/40 [==============================] - 0s 9ms/step - loss: 0.0804 - accuracy: 0.9610 - val_loss: 1.1830 - val_accuracy: 0.8020
Epoch 86/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0793 - accuracy: 0.9629
40/40 [==============================] - 0s 9ms/step - loss: 0.0793 - accuracy: 0.9629 - val_loss: 1.1668 - val_accuracy: 0.8010
Epoch 87/100
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39/40 [============================>.] - ETA: 0s - loss: 0.0798 - accuracy: 0.9622
40/40 [==============================] - 0s 6ms/step - loss: 0.0789 - accuracy: 0.9627
40/40 [==============================] - 0s 9ms/step - loss: 0.0789 - accuracy: 0.9627 - val_loss: 1.1818 - val_accuracy: 0.8040
Epoch 88/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0756 - accuracy: 0.9640
40/40 [==============================] - 0s 9ms/step - loss: 0.0756 - accuracy: 0.9640 - val_loss: 1.1776 - val_accuracy: 0.7990
Epoch 89/100
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40/40 [==============================] - 0s 6ms/step - loss: 0.0772 - accuracy: 0.9612
40/40 [==============================] - 0s 9ms/step - loss: 0.0772 - accuracy: 0.9612 - val_loss: 1.1881 - val_accuracy: 0.8010
Epoch 90/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0733 - accuracy: 0.9646
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40/40 [==============================] - 0s 6ms/step - loss: 0.0760 - accuracy: 0.9623
40/40 [==============================] - 0s 10ms/step - loss: 0.0760 - accuracy: 0.9623 - val_loss: 1.1948 - val_accuracy: 0.7990
Epoch 91/100
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40/40 [==============================] - 0s 5ms/step - loss: 0.0762 - accuracy: 0.9610
40/40 [==============================] - 0s 9ms/step - loss: 0.0762 - accuracy: 0.9610 - val_loss: 1.1951 - val_accuracy: 0.8040
Epoch 92/100
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38/40 [===========================>..] - ETA: 0s - loss: 0.0726 - accuracy: 0.9641
40/40 [==============================] - 0s 6ms/step - loss: 0.0746 - accuracy: 0.9633
40/40 [==============================] - 0s 10ms/step - loss: 0.0746 - accuracy: 0.9633 - val_loss: 1.2147 - val_accuracy: 0.8000
Epoch 93/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0675 - accuracy: 0.9673
38/40 [===========================>..] - ETA: 0s - loss: 0.0736 - accuracy: 0.9628
40/40 [==============================] - 0s 6ms/step - loss: 0.0740 - accuracy: 0.9629
40/40 [==============================] - 0s 10ms/step - loss: 0.0740 - accuracy: 0.9629 - val_loss: 1.1977 - val_accuracy: 0.8030
Epoch 94/100
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38/40 [===========================>..] - ETA: 0s - loss: 0.0721 - accuracy: 0.9630
40/40 [==============================] - 0s 6ms/step - loss: 0.0733 - accuracy: 0.9619
40/40 [==============================] - 0s 9ms/step - loss: 0.0733 - accuracy: 0.9619 - val_loss: 1.2016 - val_accuracy: 0.8040
Epoch 95/100
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27/40 [===================>..........] - ETA: 0s - loss: 0.0691 - accuracy: 0.9674
37/40 [==========================>...] - ETA: 0s - loss: 0.0754 - accuracy: 0.9628
40/40 [==============================] - 0s 6ms/step - loss: 0.0762 - accuracy: 0.9617
40/40 [==============================] - 0s 10ms/step - loss: 0.0762 - accuracy: 0.9617 - val_loss: 1.1923 - val_accuracy: 0.8020
Epoch 96/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0753 - accuracy: 0.9609
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40/40 [==============================] - 0s 6ms/step - loss: 0.0749 - accuracy: 0.9605
40/40 [==============================] - 0s 10ms/step - loss: 0.0749 - accuracy: 0.9605 - val_loss: 1.2034 - val_accuracy: 0.8020
Epoch 97/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0671 - accuracy: 0.9654
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40/40 [==============================] - 0s 6ms/step - loss: 0.0749 - accuracy: 0.9604
40/40 [==============================] - 0s 10ms/step - loss: 0.0749 - accuracy: 0.9604 - val_loss: 1.1985 - val_accuracy: 0.8010
Epoch 98/100
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37/40 [==========================>...] - ETA: 0s - loss: 0.0711 - accuracy: 0.9623
40/40 [==============================] - 0s 6ms/step - loss: 0.0726 - accuracy: 0.9612
40/40 [==============================] - 0s 9ms/step - loss: 0.0726 - accuracy: 0.9612 - val_loss: 1.2289 - val_accuracy: 0.8000
Epoch 99/100
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40/40 [==============================] - 0s 5ms/step - loss: 0.0730 - accuracy: 0.9628
40/40 [==============================] - 0s 9ms/step - loss: 0.0730 - accuracy: 0.9628 - val_loss: 1.2020 - val_accuracy: 0.8010
Epoch 100/100
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28/40 [====================>.........] - ETA: 0s - loss: 0.0637 - accuracy: 0.9688
37/40 [==========================>...] - ETA: 0s - loss: 0.0714 - accuracy: 0.9634
40/40 [==============================] - 0s 6ms/step - loss: 0.0723 - accuracy: 0.9627
40/40 [==============================] - 0s 10ms/step - loss: 0.0723 - accuracy: 0.9627 - val_loss: 1.2315 - val_accuracy: 0.8000
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-20-26Z
Training run 8/8 (flags = list(128, 1e-04, 100, 30, "tanh"))
Using run directory runs/2020-11-02T21-21-08Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 10000) %>%
+ layer_dense( units = FLAGS$n .... [TRUNCATED]
> set.seed(123)
> model %>% compile (
+ loss = 'sparse_categorical_crossentropy',
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ metr .... [TRUNCATED]
> model %>% fit (x = reuters_train, y = reuters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(reuters_val .... [TRUNCATED]
Epoch 1/30
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51/80 [==================>...........] - ETA: 0s - loss: 3.2018 - accuracy: 0.4306
61/80 [=====================>........] - ETA: 0s - loss: 3.0770 - accuracy: 0.4479
71/80 [=========================>....] - ETA: 0s - loss: 2.9641 - accuracy: 0.4580
80/80 [==============================] - 0s 5ms/step - loss: 2.8730 - accuracy: 0.4669
80/80 [==============================] - 1s 13ms/step - loss: 2.8730 - accuracy: 0.4669 - val_loss: 2.0250 - val_accuracy: 0.5410
Epoch 2/30
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27/80 [=========>....................] - ETA: 0s - loss: 1.8855 - accuracy: 0.5693
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67/80 [========================>.....] - ETA: 0s - loss: 1.7357 - accuracy: 0.6081
77/80 [===========================>..] - ETA: 0s - loss: 1.7046 - accuracy: 0.6162
80/80 [==============================] - 0s 5ms/step - loss: 1.6991 - accuracy: 0.6171
80/80 [==============================] - 1s 9ms/step - loss: 1.6991 - accuracy: 0.6171 - val_loss: 1.5059 - val_accuracy: 0.6470
Epoch 3/30
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64/80 [=======================>......] - ETA: 0s - loss: 1.3394 - accuracy: 0.7025
75/80 [===========================>..] - ETA: 0s - loss: 1.3241 - accuracy: 0.7047
80/80 [==============================] - 0s 5ms/step - loss: 1.3211 - accuracy: 0.7050
80/80 [==============================] - 1s 7ms/step - loss: 1.3211 - accuracy: 0.7050 - val_loss: 1.2829 - val_accuracy: 0.7040
Epoch 4/30
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11/80 [===>..........................] - ETA: 0s - loss: 1.1858 - accuracy: 0.7382
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32/80 [===========>..................] - ETA: 0s - loss: 1.1398 - accuracy: 0.7462
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52/80 [==================>...........] - ETA: 0s - loss: 1.1209 - accuracy: 0.7492
62/80 [======================>.......] - ETA: 0s - loss: 1.1035 - accuracy: 0.7523
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80/80 [==============================] - 0s 5ms/step - loss: 1.0956 - accuracy: 0.7548
80/80 [==============================] - 1s 7ms/step - loss: 1.0956 - accuracy: 0.7548 - val_loss: 1.1529 - val_accuracy: 0.7410
Epoch 5/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.9303 - accuracy: 0.7985
80/80 [==============================] - 1s 7ms/step - loss: 0.9303 - accuracy: 0.7985 - val_loss: 1.0654 - val_accuracy: 0.7660
Epoch 6/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.7963 - accuracy: 0.8348
80/80 [==============================] - 1s 7ms/step - loss: 0.7963 - accuracy: 0.8348 - val_loss: 1.0035 - val_accuracy: 0.7850
Epoch 7/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.6832 - accuracy: 0.8634
80/80 [==============================] - 1s 7ms/step - loss: 0.6832 - accuracy: 0.8634 - val_loss: 0.9566 - val_accuracy: 0.7970
Epoch 8/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.5886 - accuracy: 0.8831
80/80 [==============================] - 1s 7ms/step - loss: 0.5886 - accuracy: 0.8831 - val_loss: 0.9216 - val_accuracy: 0.8040
Epoch 9/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.5074 - accuracy: 0.9010
80/80 [==============================] - 1s 7ms/step - loss: 0.5074 - accuracy: 0.9010 - val_loss: 0.8970 - val_accuracy: 0.8060
Epoch 10/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.4390 - accuracy: 0.9181
80/80 [==============================] - 1s 7ms/step - loss: 0.4390 - accuracy: 0.9181 - val_loss: 0.8805 - val_accuracy: 0.8140
Epoch 11/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.3824 - accuracy: 0.9271
80/80 [==============================] - 1s 7ms/step - loss: 0.3824 - accuracy: 0.9271 - val_loss: 0.8682 - val_accuracy: 0.8120
Epoch 12/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.3336 - accuracy: 0.9355
80/80 [==============================] - 1s 8ms/step - loss: 0.3336 - accuracy: 0.9355 - val_loss: 0.8627 - val_accuracy: 0.8120
Epoch 13/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.2942 - accuracy: 0.9402
80/80 [==============================] - 1s 7ms/step - loss: 0.2942 - accuracy: 0.9402 - val_loss: 0.8555 - val_accuracy: 0.8100
Epoch 14/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.2603 - accuracy: 0.9435
80/80 [==============================] - 1s 8ms/step - loss: 0.2603 - accuracy: 0.9435 - val_loss: 0.8569 - val_accuracy: 0.8070
Epoch 15/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.2324 - accuracy: 0.9473
80/80 [==============================] - 1s 8ms/step - loss: 0.2324 - accuracy: 0.9473 - val_loss: 0.8594 - val_accuracy: 0.8150
Epoch 16/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.2100 - accuracy: 0.9503
80/80 [==============================] - 1s 8ms/step - loss: 0.2100 - accuracy: 0.9503 - val_loss: 0.8636 - val_accuracy: 0.8050
Epoch 17/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1902 - accuracy: 0.9518
80/80 [==============================] - 1s 8ms/step - loss: 0.1902 - accuracy: 0.9518 - val_loss: 0.8633 - val_accuracy: 0.8110
Epoch 18/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1742 - accuracy: 0.9541
80/80 [==============================] - 1s 8ms/step - loss: 0.1742 - accuracy: 0.9541 - val_loss: 0.8661 - val_accuracy: 0.8090
Epoch 19/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1607 - accuracy: 0.9549
80/80 [==============================] - 1s 8ms/step - loss: 0.1607 - accuracy: 0.9549 - val_loss: 0.8822 - val_accuracy: 0.8040
Epoch 20/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1482 - accuracy: 0.9564
80/80 [==============================] - 1s 8ms/step - loss: 0.1482 - accuracy: 0.9564 - val_loss: 0.8894 - val_accuracy: 0.8110
Epoch 21/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1396 - accuracy: 0.9568
80/80 [==============================] - 1s 8ms/step - loss: 0.1396 - accuracy: 0.9568 - val_loss: 0.8881 - val_accuracy: 0.8060
Epoch 22/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1311 - accuracy: 0.9568
80/80 [==============================] - 1s 8ms/step - loss: 0.1311 - accuracy: 0.9568 - val_loss: 0.8949 - val_accuracy: 0.8050
Epoch 23/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1237 - accuracy: 0.9570
80/80 [==============================] - 1s 8ms/step - loss: 0.1237 - accuracy: 0.9570 - val_loss: 0.9085 - val_accuracy: 0.8020
Epoch 24/30
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80/80 [==============================] - 0s 6ms/step - loss: 0.1189 - accuracy: 0.9567
80/80 [==============================] - 1s 8ms/step - loss: 0.1189 - accuracy: 0.9567 - val_loss: 0.9051 - val_accuracy: 0.8110
Epoch 25/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1136 - accuracy: 0.9579
80/80 [==============================] - 1s 7ms/step - loss: 0.1136 - accuracy: 0.9579 - val_loss: 0.9213 - val_accuracy: 0.7980
Epoch 26/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1085 - accuracy: 0.9587
80/80 [==============================] - 1s 8ms/step - loss: 0.1085 - accuracy: 0.9587 - val_loss: 0.9157 - val_accuracy: 0.8070
Epoch 27/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1048 - accuracy: 0.9567
80/80 [==============================] - 1s 8ms/step - loss: 0.1048 - accuracy: 0.9567 - val_loss: 0.9190 - val_accuracy: 0.8040
Epoch 28/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.1016 - accuracy: 0.9582
80/80 [==============================] - 1s 7ms/step - loss: 0.1016 - accuracy: 0.9582 - val_loss: 0.9202 - val_accuracy: 0.8080
Epoch 29/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.0985 - accuracy: 0.9573
80/80 [==============================] - 1s 8ms/step - loss: 0.0985 - accuracy: 0.9573 - val_loss: 0.9232 - val_accuracy: 0.8040
Epoch 30/30
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80/80 [==============================] - 0s 5ms/step - loss: 0.0953 - accuracy: 0.9587
80/80 [==============================] - 1s 8ms/step - loss: 0.0953 - accuracy: 0.9587 - val_loss: 0.9304 - val_accuracy: 0.8010
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T21-21-08Z
runs
Data frame: 8 x 25
# ... with 20 more columns:
# flag_nodes, flag_batch_size, flag_activation, flag_learning_rate, flag_epochs,
# epochs, epochs_completed, metrics, model, loss_function, optimizer,
# learning_rate, script, start, end, completed, output, source_code, context, type
Q3. (5 pts) Now use ALL the training data in reuters$train (i.e., train + validation data) to train an ANN with the best hyper- parameter combination you found after tuning in the previous question. Compute the accuracy of this model on the test set.
reuters_train = one_hot_encoding(reuters$train$x)
reuters_test = one_hot_encoding(reuters$test$x)
model <- keras_model_sequential()
model %>%
layer_dense( units = 128, activation = "tanh", input_shape = 10000) %>%
layer_dense( units = 128, activation = "tanh") %>%
layer_dense( units = 128, activation = "tanh") %>%
layer_dense(units = 46, activation = 'softmax')
set.seed(123)
model %>% compile (
loss = 'sparse_categorical_crossentropy',
optimizer = optimizer_adam(lr=0.0001),
metrics = 'accuracy')
model %>% fit (x = reuters_train, y = reuters$train$y, epochs = 30, batch_size = 100)
Epoch 1/30
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90/90 [==============================] - 0s 5ms/step - loss: 2.7786 - accuracy: 0.4804
90/90 [==============================] - 1s 11ms/step - loss: 2.7786 - accuracy: 0.4804
Epoch 2/30
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90/90 [==============================] - 0s 5ms/step - loss: 1.6191 - accuracy: 0.6428
90/90 [==============================] - 1s 7ms/step - loss: 1.6191 - accuracy: 0.6428
Epoch 3/30
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90/90 [==============================] - 1s 6ms/step - loss: 1.2556 - accuracy: 0.7164
90/90 [==============================] - 1s 7ms/step - loss: 1.2556 - accuracy: 0.7164
Epoch 4/30
1/90 [..............................] - ETA: 0s - loss: 1.0141 - accuracy: 0.8100
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90/90 [==============================] - 0s 5ms/step - loss: 1.0318 - accuracy: 0.7723
90/90 [==============================] - 1s 6ms/step - loss: 1.0318 - accuracy: 0.7723
Epoch 5/30
1/90 [..............................] - ETA: 0s - loss: 1.0008 - accuracy: 0.7800
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90/90 [==============================] - 0s 5ms/step - loss: 0.8626 - accuracy: 0.8191
90/90 [==============================] - 1s 7ms/step - loss: 0.8626 - accuracy: 0.8191
Epoch 6/30
1/90 [..............................] - ETA: 0s - loss: 0.7091 - accuracy: 0.8300
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90/90 [==============================] - 0s 5ms/step - loss: 0.7263 - accuracy: 0.8542
90/90 [==============================] - 1s 6ms/step - loss: 0.7263 - accuracy: 0.8542
Epoch 7/30
1/90 [..............................] - ETA: 0s - loss: 0.7857 - accuracy: 0.8600
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90/90 [==============================] - 0s 5ms/step - loss: 0.6140 - accuracy: 0.8803
90/90 [==============================] - 1s 6ms/step - loss: 0.6140 - accuracy: 0.8803
Epoch 8/30
1/90 [..............................] - ETA: 0s - loss: 0.7115 - accuracy: 0.8900
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90/90 [==============================] - 0s 5ms/step - loss: 0.5226 - accuracy: 0.8985
90/90 [==============================] - 1s 6ms/step - loss: 0.5226 - accuracy: 0.8985
Epoch 9/30
1/90 [..............................] - ETA: 0s - loss: 0.3517 - accuracy: 0.9500
11/90 [==>...........................] - ETA: 0s - loss: 0.3799 - accuracy: 0.9364
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90/90 [==============================] - 0s 5ms/step - loss: 0.4489 - accuracy: 0.9133
90/90 [==============================] - 1s 6ms/step - loss: 0.4489 - accuracy: 0.9133
Epoch 10/30
1/90 [..............................] - ETA: 0s - loss: 0.3058 - accuracy: 0.9500
11/90 [==>...........................] - ETA: 0s - loss: 0.3391 - accuracy: 0.9345
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90/90 [==============================] - 1s 7ms/step - loss: 0.3875 - accuracy: 0.9244
90/90 [==============================] - 1s 9ms/step - loss: 0.3875 - accuracy: 0.9244
Epoch 11/30
1/90 [..............................] - ETA: 0s - loss: 0.2561 - accuracy: 0.9400
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90/90 [==============================] - 0s 5ms/step - loss: 0.3368 - accuracy: 0.9339
90/90 [==============================] - 1s 6ms/step - loss: 0.3368 - accuracy: 0.9339
Epoch 12/30
1/90 [..............................] - ETA: 0s - loss: 0.4365 - accuracy: 0.8900
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90/90 [==============================] - 0s 5ms/step - loss: 0.2962 - accuracy: 0.9377
90/90 [==============================] - 1s 6ms/step - loss: 0.2962 - accuracy: 0.9377
Epoch 13/30
1/90 [..............................] - ETA: 0s - loss: 0.1800 - accuracy: 0.9700
12/90 [===>..........................] - ETA: 0s - loss: 0.2578 - accuracy: 0.9533
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90/90 [==============================] - 0s 5ms/step - loss: 0.2627 - accuracy: 0.9448
90/90 [==============================] - 1s 6ms/step - loss: 0.2627 - accuracy: 0.9448
Epoch 14/30
1/90 [..............................] - ETA: 0s - loss: 0.1498 - accuracy: 0.9700
11/90 [==>...........................] - ETA: 0s - loss: 0.2092 - accuracy: 0.9527
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90/90 [==============================] - 0s 5ms/step - loss: 0.2339 - accuracy: 0.9463
90/90 [==============================] - 1s 6ms/step - loss: 0.2339 - accuracy: 0.9463
Epoch 15/30
1/90 [..............................] - ETA: 0s - loss: 0.1743 - accuracy: 0.9900
11/90 [==>...........................] - ETA: 0s - loss: 0.1930 - accuracy: 0.9645
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90/90 [==============================] - 0s 5ms/step - loss: 0.2105 - accuracy: 0.9495
90/90 [==============================] - 1s 6ms/step - loss: 0.2105 - accuracy: 0.9495
Epoch 16/30
1/90 [..............................] - ETA: 0s - loss: 0.2607 - accuracy: 0.9400
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90/90 [==============================] - 0s 5ms/step - loss: 0.1917 - accuracy: 0.9490
90/90 [==============================] - 1s 6ms/step - loss: 0.1917 - accuracy: 0.9490
Epoch 17/30
1/90 [..............................] - ETA: 0s - loss: 0.1309 - accuracy: 0.9700
11/90 [==>...........................] - ETA: 0s - loss: 0.1627 - accuracy: 0.9582
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90/90 [==============================] - 0s 5ms/step - loss: 0.1759 - accuracy: 0.9509
90/90 [==============================] - 1s 6ms/step - loss: 0.1759 - accuracy: 0.9509
Epoch 18/30
1/90 [..............................] - ETA: 0s - loss: 0.1302 - accuracy: 0.9800
11/90 [==>...........................] - ETA: 0s - loss: 0.1563 - accuracy: 0.9573
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90/90 [==============================] - 0s 5ms/step - loss: 0.1638 - accuracy: 0.9532
90/90 [==============================] - 1s 6ms/step - loss: 0.1638 - accuracy: 0.9532
Epoch 19/30
1/90 [..............................] - ETA: 0s - loss: 0.1138 - accuracy: 0.9600
11/90 [==>...........................] - ETA: 0s - loss: 0.1326 - accuracy: 0.9645
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90/90 [==============================] - 0s 5ms/step - loss: 0.1516 - accuracy: 0.9539
90/90 [==============================] - 1s 6ms/step - loss: 0.1516 - accuracy: 0.9539
Epoch 20/30
1/90 [..............................] - ETA: 0s - loss: 0.1230 - accuracy: 0.9200
11/90 [==>...........................] - ETA: 0s - loss: 0.1157 - accuracy: 0.9664
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84/90 [===========================>..] - ETA: 0s - loss: 0.1424 - accuracy: 0.9539
90/90 [==============================] - 0s 5ms/step - loss: 0.1416 - accuracy: 0.9541
90/90 [==============================] - 1s 6ms/step - loss: 0.1416 - accuracy: 0.9541
Epoch 21/30
1/90 [..............................] - ETA: 0s - loss: 0.1267 - accuracy: 0.9600
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86/90 [===========================>..] - ETA: 0s - loss: 0.1327 - accuracy: 0.9552
90/90 [==============================] - 0s 5ms/step - loss: 0.1337 - accuracy: 0.9547
90/90 [==============================] - 1s 6ms/step - loss: 0.1337 - accuracy: 0.9547
Epoch 22/30
1/90 [..............................] - ETA: 0s - loss: 0.1211 - accuracy: 0.9500
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90/90 [==============================] - 0s 5ms/step - loss: 0.1259 - accuracy: 0.9536
90/90 [==============================] - 1s 6ms/step - loss: 0.1259 - accuracy: 0.9536
Epoch 23/30
1/90 [..............................] - ETA: 0s - loss: 0.1802 - accuracy: 0.9100
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90/90 [==============================] - 0s 5ms/step - loss: 0.1211 - accuracy: 0.9530
90/90 [==============================] - 1s 6ms/step - loss: 0.1211 - accuracy: 0.9530
Epoch 24/30
1/90 [..............................] - ETA: 0s - loss: 0.0888 - accuracy: 0.9700
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90/90 [==============================] - 1s 6ms/step - loss: 0.1166 - accuracy: 0.9546
90/90 [==============================] - 1s 7ms/step - loss: 0.1166 - accuracy: 0.9546
Epoch 25/30
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30/90 [=========>....................] - ETA: 0s - loss: 0.1001 - accuracy: 0.9643
40/90 [============>.................] - ETA: 0s - loss: 0.1038 - accuracy: 0.9622
50/90 [===============>..............] - ETA: 0s - loss: 0.1004 - accuracy: 0.9628
60/90 [===================>..........] - ETA: 0s - loss: 0.1041 - accuracy: 0.9608
70/90 [======================>.......] - ETA: 0s - loss: 0.1080 - accuracy: 0.9584
80/90 [=========================>....] - ETA: 0s - loss: 0.1085 - accuracy: 0.9578
90/90 [==============================] - 0s 5ms/step - loss: 0.1112 - accuracy: 0.9564
90/90 [==============================] - 1s 6ms/step - loss: 0.1112 - accuracy: 0.9564
Epoch 26/30
1/90 [..............................] - ETA: 0s - loss: 0.1077 - accuracy: 0.9600
11/90 [==>...........................] - ETA: 0s - loss: 0.0928 - accuracy: 0.9655
21/90 [======>.......................] - ETA: 0s - loss: 0.0947 - accuracy: 0.9633
31/90 [=========>....................] - ETA: 0s - loss: 0.0907 - accuracy: 0.9665
41/90 [============>.................] - ETA: 0s - loss: 0.0928 - accuracy: 0.9654
50/90 [===============>..............] - ETA: 0s - loss: 0.0977 - accuracy: 0.9632
59/90 [==================>...........] - ETA: 0s - loss: 0.0996 - accuracy: 0.9619
69/90 [======================>.......] - ETA: 0s - loss: 0.1050 - accuracy: 0.9578
78/90 [=========================>....] - ETA: 0s - loss: 0.1055 - accuracy: 0.9567
88/90 [============================>.] - ETA: 0s - loss: 0.1075 - accuracy: 0.9559
90/90 [==============================] - 0s 5ms/step - loss: 0.1078 - accuracy: 0.9556
90/90 [==============================] - 1s 7ms/step - loss: 0.1078 - accuracy: 0.9556
Epoch 27/30
1/90 [..............................] - ETA: 0s - loss: 0.1206 - accuracy: 0.9700
11/90 [==>...........................] - ETA: 0s - loss: 0.0980 - accuracy: 0.9627
21/90 [======>.......................] - ETA: 0s - loss: 0.1007 - accuracy: 0.9590
31/90 [=========>....................] - ETA: 0s - loss: 0.0963 - accuracy: 0.9587
41/90 [============>.................] - ETA: 0s - loss: 0.0956 - accuracy: 0.9595
51/90 [================>.............] - ETA: 0s - loss: 0.0990 - accuracy: 0.9576
61/90 [===================>..........] - ETA: 0s - loss: 0.0995 - accuracy: 0.9570
71/90 [======================>.......] - ETA: 0s - loss: 0.0990 - accuracy: 0.9570
81/90 [==========================>...] - ETA: 0s - loss: 0.1003 - accuracy: 0.9557
90/90 [==============================] - 0s 5ms/step - loss: 0.1039 - accuracy: 0.9544
90/90 [==============================] - 1s 6ms/step - loss: 0.1039 - accuracy: 0.9544
Epoch 28/30
1/90 [..............................] - ETA: 0s - loss: 0.0906 - accuracy: 0.9500
11/90 [==>...........................] - ETA: 0s - loss: 0.0799 - accuracy: 0.9700
21/90 [======>.......................] - ETA: 0s - loss: 0.0766 - accuracy: 0.9700
31/90 [=========>....................] - ETA: 0s - loss: 0.0820 - accuracy: 0.9655
41/90 [============>.................] - ETA: 0s - loss: 0.0825 - accuracy: 0.9666
51/90 [================>.............] - ETA: 0s - loss: 0.0842 - accuracy: 0.9655
61/90 [===================>..........] - ETA: 0s - loss: 0.0942 - accuracy: 0.9615
71/90 [======================>.......] - ETA: 0s - loss: 0.0967 - accuracy: 0.9596
81/90 [==========================>...] - ETA: 0s - loss: 0.0997 - accuracy: 0.9573
90/90 [==============================] - 0s 5ms/step - loss: 0.1020 - accuracy: 0.9557
90/90 [==============================] - 1s 6ms/step - loss: 0.1020 - accuracy: 0.9557
Epoch 29/30
1/90 [..............................] - ETA: 0s - loss: 0.0597 - accuracy: 0.9800
11/90 [==>...........................] - ETA: 0s - loss: 0.0934 - accuracy: 0.9700
20/90 [=====>........................] - ETA: 0s - loss: 0.0956 - accuracy: 0.9615
29/90 [========>.....................] - ETA: 0s - loss: 0.0992 - accuracy: 0.9572
39/90 [============>.................] - ETA: 0s - loss: 0.0971 - accuracy: 0.9577
49/90 [===============>..............] - ETA: 0s - loss: 0.0960 - accuracy: 0.9584
59/90 [==================>...........] - ETA: 0s - loss: 0.0948 - accuracy: 0.9580
69/90 [======================>.......] - ETA: 0s - loss: 0.0949 - accuracy: 0.9572
79/90 [=========================>....] - ETA: 0s - loss: 0.0969 - accuracy: 0.9562
89/90 [============================>.] - ETA: 0s - loss: 0.0976 - accuracy: 0.9557
90/90 [==============================] - 0s 5ms/step - loss: 0.0987 - accuracy: 0.9554
90/90 [==============================] - 1s 7ms/step - loss: 0.0987 - accuracy: 0.9554
Epoch 30/30
1/90 [..............................] - ETA: 0s - loss: 0.0773 - accuracy: 0.9600
11/90 [==>...........................] - ETA: 0s - loss: 0.0748 - accuracy: 0.9700
21/90 [======>.......................] - ETA: 0s - loss: 0.0824 - accuracy: 0.9662
32/90 [=========>....................] - ETA: 0s - loss: 0.0854 - accuracy: 0.9650
42/90 [=============>................] - ETA: 0s - loss: 0.0875 - accuracy: 0.9629
52/90 [================>.............] - ETA: 0s - loss: 0.0869 - accuracy: 0.9623
63/90 [====================>.........] - ETA: 0s - loss: 0.0871 - accuracy: 0.9617
73/90 [=======================>......] - ETA: 0s - loss: 0.0878 - accuracy: 0.9614
83/90 [==========================>...] - ETA: 0s - loss: 0.0922 - accuracy: 0.9583
90/90 [==============================] - 0s 5ms/step - loss: 0.0954 - accuracy: 0.9564
90/90 [==============================] - 1s 6ms/step - loss: 0.0954 - accuracy: 0.9564
model %>% evaluate(x = reuters_test, y = reuters$test$y)
1/71 [..............................] - ETA: 0s - loss: 0.6431 - accuracy: 0.9062
33/71 [============>.................] - ETA: 0s - loss: 0.9869 - accuracy: 0.7936
63/71 [=========================>....] - ETA: 0s - loss: 0.9889 - accuracy: 0.7961
71/71 [==============================] - 0s 2ms/step - loss: 1.0126 - accuracy: 0.7903
71/71 [==============================] - 0s 2ms/step - loss: 1.0126 - accuracy: 0.7903
loss accuracy
1.0126262 0.7902939
hitters = read.csv("hitters.csv")
str(hitters)
'data.frame': 322 obs. of 20 variables:
$ AtBat : int 293 315 479 496 321 594 185 298 323 401 ...
$ Hits : int 66 81 130 141 87 169 37 73 81 92 ...
$ HmRun : int 1 7 18 20 10 4 1 0 6 17 ...
$ Runs : int 30 24 66 65 39 74 23 24 26 49 ...
$ RBI : int 29 38 72 78 42 51 8 24 32 66 ...
$ Walks : int 14 39 76 37 30 35 21 7 8 65 ...
$ Years : int 1 14 3 11 2 11 2 3 2 13 ...
$ CAtBat : int 293 3449 1624 5628 396 4408 214 509 341 5206 ...
$ CHits : int 66 835 457 1575 101 1133 42 108 86 1332 ...
$ CHmRun : int 1 69 63 225 12 19 1 0 6 253 ...
$ CRuns : int 30 321 224 828 48 501 30 41 32 784 ...
$ CRBI : int 29 414 266 838 46 336 9 37 34 890 ...
$ CWalks : int 14 375 263 354 33 194 24 12 8 866 ...
$ League : chr "A" "N" "A" "N" ...
$ Division : chr "E" "W" "W" "E" ...
$ PutOuts : int 446 632 880 200 805 282 76 121 143 0 ...
$ Assists : int 33 43 82 11 40 421 127 283 290 0 ...
$ Errors : int 20 10 14 3 4 25 7 9 19 0 ...
$ Salary : num NA 475 480 500 91.5 750 70 100 75 1100 ...
$ NewLeague: chr "A" "N" "A" "N" ...
summary(hitters)
AtBat Hits HmRun Runs RBI
Min. : 16.0 Min. : 1 Min. : 0.00 Min. : 0.00 Min. : 0.00
1st Qu.:255.2 1st Qu.: 64 1st Qu.: 4.00 1st Qu.: 30.25 1st Qu.: 28.00
Median :379.5 Median : 96 Median : 8.00 Median : 48.00 Median : 44.00
Mean :380.9 Mean :101 Mean :10.77 Mean : 50.91 Mean : 48.03
3rd Qu.:512.0 3rd Qu.:137 3rd Qu.:16.00 3rd Qu.: 69.00 3rd Qu.: 64.75
Max. :687.0 Max. :238 Max. :40.00 Max. :130.00 Max. :121.00
Walks Years CAtBat CHits CHmRun
Min. : 0.00 Min. : 1.000 Min. : 19.0 Min. : 4.0 Min. : 0.00
1st Qu.: 22.00 1st Qu.: 4.000 1st Qu.: 816.8 1st Qu.: 209.0 1st Qu.: 14.00
Median : 35.00 Median : 6.000 Median : 1928.0 Median : 508.0 Median : 37.50
Mean : 38.74 Mean : 7.444 Mean : 2648.7 Mean : 717.6 Mean : 69.49
3rd Qu.: 53.00 3rd Qu.:11.000 3rd Qu.: 3924.2 3rd Qu.:1059.2 3rd Qu.: 90.00
Max. :105.00 Max. :24.000 Max. :14053.0 Max. :4256.0 Max. :548.00
CRuns CRBI CWalks League Division
Min. : 1.0 Min. : 0.00 Min. : 0.00 Length:322 Length:322
1st Qu.: 100.2 1st Qu.: 88.75 1st Qu.: 67.25 Class :character Class :character
Median : 247.0 Median : 220.50 Median : 170.50 Mode :character Mode :character
Mean : 358.8 Mean : 330.12 Mean : 260.24
3rd Qu.: 526.2 3rd Qu.: 426.25 3rd Qu.: 339.25
Max. :2165.0 Max. :1659.00 Max. :1566.00
PutOuts Assists Errors Salary NewLeague
Min. : 0.0 Min. : 0.0 Min. : 0.00 Min. : 67.5 Length:322
1st Qu.: 109.2 1st Qu.: 7.0 1st Qu.: 3.00 1st Qu.: 190.0 Class :character
Median : 212.0 Median : 39.5 Median : 6.00 Median : 425.0 Mode :character
Mean : 288.9 Mean :106.9 Mean : 8.04 Mean : 535.9
3rd Qu.: 325.0 3rd Qu.:166.0 3rd Qu.:11.00 3rd Qu.: 750.0
Max. :1378.0 Max. :492.0 Max. :32.00 Max. :2460.0
NA's :59
hist(hitters$Salary)
hitters_clean = hitters[!is.na(hitters$Salary),]
plot(hitters_clean[ , c(19, 1:4)])
plot(hitters_clean[ , c(19, 5:9)])
plot(hitters_clean[ , c(19, 10:13)])
plot(hitters_clean[ , c(19, 16:18)])
boxplot(Salary~League,data = hitters_clean)
boxplot(Salary~Division,data = hitters_clean)
boxplot(Salary~NewLeague,data = hitters_clean)
t.test(Salary~League, data = hitters_clean)
Welch Two Sample t-test
data: Salary by League
t = 0.23157, df = 260.26, p-value = 0.8171
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-96.66039 122.42448
sample estimates:
mean in group A mean in group N
541.9995 529.1175
t.test(Salary~Division,data = hitters_clean)
Welch Two Sample t-test
data: Salary by Division
t = 3.145, df = 218.46, p-value = 0.001892
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
64.73206 282.05692
sample estimates:
mean in group E mean in group W
624.2714 450.8769
t.test(Salary~NewLeague,data = hitters_clean)
Welch Two Sample t-test
data: Salary by NewLeague
t = 0.045921, df = 258.07, p-value = 0.9634
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-107.1832 112.3016
sample estimates:
mean in group A mean in group N
537.1130 534.5539
cor(hitters_clean$Salary, y=hitters_clean[-c(19, 15, 14, 20)])
AtBat Hits HmRun Runs RBI Walks Years CAtBat
[1,] 0.3947709 0.4386747 0.3430281 0.4198586 0.4494571 0.4438673 0.400657 0.5261353
CHits CHmRun CRuns CRBI CWalks PutOuts Assists Errors
[1,] 0.5489096 0.5249306 0.5626777 0.5669657 0.489822 0.3004804 0.02543614 -0.005400702
CAtBat, CHits, CHmRun, CRuns, and CRBI have correlations greater than .5
set.seed(1)
inTrain = createDataPartition(hitters_clean$Salary, p=0.9, list=FALSE)
hitters_train = hitters_clean[inTrain,]
hitters_test = hitters_clean[-inTrain,]
hitters_train$NewLeague = ifelse(hitters_train$NewLeague == "N", 1, 0)
hitters_train$Division = ifelse(hitters_train$Division == "W", 1, 0)
hitters_train$League = ifelse(hitters_train$League == "N", 1, 0)
hitters_train$Salary = log(hitters_train$Salary)
toTrain = createDataPartition(hitters_train$Salary, p=0.9, list=FALSE)
hitters_train = hitters_train[toTrain , ]
hitters_val = hitters_train[-toTrain , ]
9 cont. (5 pt) Create an ANN model to predict log(salary) from other attributes. Use at least two hidden layers. Use tfruns to tune your model’s hyper-parameters including, the number of nodes in each hidden layer, the activation function in each hidden layer, batch_size, learning_rate, and the number of epochs). Validate each model on the validation set. Answer the following questions:
library(tfruns)
runs <- tuning_run("hitters.R",
flags = list (
nodes = c(64, 128, 392),
learning_rate = c(0.01, 0.05, 0.001, 0.0001),
batch_size = c(100, 200, 500, 1000),
epochs = c(30, 50, 100),
activation = c("relu","sigmoid","tanh")
), sample = 0.02)
432 total combinations of flags (sampled to 8 combinations)
y
Training run 1/8 (flags = list(392, 1e-04, 500, 30, "tanh"))
Using run directory runs/2020-11-02T19-38-41Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/30
1/1 [==============================] - 0s 12us/step - loss: 34.4054
1/1 [==============================] - 1s 581ms/step - loss: 34.4054 - val_loss: 35.5684
Epoch 2/30
1/1 [==============================] - 0s 14us/step - loss: 34.2553
1/1 [==============================] - 0s 140ms/step - loss: 34.2553 - val_loss: 35.4413
Epoch 3/30
1/1 [==============================] - 0s 14us/step - loss: 34.1059
1/1 [==============================] - 0s 134ms/step - loss: 34.1059 - val_loss: 35.3146
Epoch 4/30
1/1 [==============================] - 0s 13us/step - loss: 33.9570
1/1 [==============================] - 0s 136ms/step - loss: 33.9570 - val_loss: 35.1884
Epoch 5/30
1/1 [==============================] - 0s 13us/step - loss: 33.8087
1/1 [==============================] - 0s 137ms/step - loss: 33.8087 - val_loss: 35.0625
Epoch 6/30
1/1 [==============================] - 0s 14us/step - loss: 33.6610
1/1 [==============================] - 0s 137ms/step - loss: 33.6610 - val_loss: 34.9370
Epoch 7/30
1/1 [==============================] - 0s 11us/step - loss: 33.5138
1/1 [==============================] - 0s 136ms/step - loss: 33.5138 - val_loss: 34.8119
Epoch 8/30
1/1 [==============================] - 0s 11us/step - loss: 33.3672
1/1 [==============================] - 0s 133ms/step - loss: 33.3672 - val_loss: 34.6872
Epoch 9/30
1/1 [==============================] - 0s 15us/step - loss: 33.2211
1/1 [==============================] - 0s 135ms/step - loss: 33.2211 - val_loss: 34.5628
Epoch 10/30
1/1 [==============================] - 0s 14us/step - loss: 33.0755
1/1 [==============================] - 0s 135ms/step - loss: 33.0755 - val_loss: 34.4387
Epoch 11/30
1/1 [==============================] - 0s 13us/step - loss: 32.9305
1/1 [==============================] - 0s 143ms/step - loss: 32.9305 - val_loss: 34.3151
Epoch 12/30
1/1 [==============================] - 0s 13us/step - loss: 32.7860
1/1 [==============================] - 0s 253ms/step - loss: 32.7860 - val_loss: 34.1917
Epoch 13/30
1/1 [==============================] - 0s 13us/step - loss: 32.6419
1/1 [==============================] - 0s 134ms/step - loss: 32.6419 - val_loss: 34.0687
Epoch 14/30
1/1 [==============================] - 0s 14us/step - loss: 32.4984
1/1 [==============================] - 0s 133ms/step - loss: 32.4984 - val_loss: 33.9460
Epoch 15/30
1/1 [==============================] - 0s 12us/step - loss: 32.3553
1/1 [==============================] - 0s 135ms/step - loss: 32.3553 - val_loss: 33.8236
Epoch 16/30
1/1 [==============================] - 0s 15us/step - loss: 32.2127
1/1 [==============================] - 0s 137ms/step - loss: 32.2127 - val_loss: 33.7015
Epoch 17/30
1/1 [==============================] - 0s 13us/step - loss: 32.0706
1/1 [==============================] - 0s 135ms/step - loss: 32.0706 - val_loss: 33.5797
Epoch 18/30
1/1 [==============================] - 0s 14us/step - loss: 31.9289
1/1 [==============================] - 0s 154ms/step - loss: 31.9289 - val_loss: 33.4582
Epoch 19/30
1/1 [==============================] - 0s 14us/step - loss: 31.7876
1/1 [==============================] - 0s 139ms/step - loss: 31.7876 - val_loss: 33.3369
Epoch 20/30
1/1 [==============================] - 0s 15us/step - loss: 31.6468
1/1 [==============================] - 0s 137ms/step - loss: 31.6468 - val_loss: 33.2160
Epoch 21/30
1/1 [==============================] - 0s 17us/step - loss: 31.5064
1/1 [==============================] - 0s 144ms/step - loss: 31.5064 - val_loss: 33.0953
Epoch 22/30
1/1 [==============================] - 0s 13us/step - loss: 31.3665
1/1 [==============================] - 0s 135ms/step - loss: 31.3665 - val_loss: 32.9749
Epoch 23/30
1/1 [==============================] - 0s 14us/step - loss: 31.2269
1/1 [==============================] - 0s 135ms/step - loss: 31.2269 - val_loss: 32.8547
Epoch 24/30
1/1 [==============================] - 0s 14us/step - loss: 31.0877
1/1 [==============================] - 0s 135ms/step - loss: 31.0877 - val_loss: 32.7348
Epoch 25/30
1/1 [==============================] - 0s 14us/step - loss: 30.9489
1/1 [==============================] - 0s 136ms/step - loss: 30.9489 - val_loss: 32.6151
Epoch 26/30
1/1 [==============================] - 0s 13us/step - loss: 30.8106
1/1 [==============================] - 0s 134ms/step - loss: 30.8106 - val_loss: 32.4957
Epoch 27/30
1/1 [==============================] - 0s 13us/step - loss: 30.6726
1/1 [==============================] - 0s 136ms/step - loss: 30.6726 - val_loss: 32.3765
Epoch 28/30
1/1 [==============================] - 0s 13us/step - loss: 30.5349
1/1 [==============================] - 0s 135ms/step - loss: 30.5349 - val_loss: 32.2575
Epoch 29/30
1/1 [==============================] - 0s 12us/step - loss: 30.3977
1/1 [==============================] - 0s 132ms/step - loss: 30.3977 - val_loss: 32.1387
Epoch 30/30
1/1 [==============================] - 0s 10us/step - loss: 30.2607
1/1 [==============================] - 0s 136ms/step - loss: 30.2607 - val_loss: 32.0202
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-38-41Z
Training run 2/8 (flags = list(128, 1e-04, 200, 30, "sigmoid"))
Using run directory runs/2020-11-02T19-38-46Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/30
1/2 [==============>...............] - ETA: 0s - loss: 32.5841
2/2 [==============================] - 0s 705us/step - loss: 32.4016
2/2 [==============================] - 1s 291ms/step - loss: 32.4016 - val_loss: 32.4801
Epoch 2/30
1/2 [==============>...............] - ETA: 0s - loss: 31.6476
2/2 [==============================] - 0s 887us/step - loss: 31.4588
2/2 [==============================] - 0s 71ms/step - loss: 31.4588 - val_loss: 31.5503
Epoch 3/30
1/2 [==============>...............] - ETA: 0s - loss: 30.3406
2/2 [==============================] - 0s 791us/step - loss: 30.5435
2/2 [==============================] - 0s 68ms/step - loss: 30.5435 - val_loss: 30.6138
Epoch 4/30
1/2 [==============>...............] - ETA: 0s - loss: 29.8690
2/2 [==============================] - 0s 975us/step - loss: 29.6275
2/2 [==============================] - 0s 71ms/step - loss: 29.6275 - val_loss: 29.7450
Epoch 5/30
1/2 [==============>...............] - ETA: 0s - loss: 28.6188
2/2 [==============================] - 0s 1ms/step - loss: 28.7723
2/2 [==============================] - 0s 72ms/step - loss: 28.7723 - val_loss: 28.8649
Epoch 6/30
1/2 [==============>...............] - ETA: 0s - loss: 28.0664
2/2 [==============================] - 0s 793us/step - loss: 27.9112
2/2 [==============================] - 0s 67ms/step - loss: 27.9112 - val_loss: 28.0408
Epoch 7/30
1/2 [==============>...............] - ETA: 0s - loss: 27.2473
2/2 [==============================] - 0s 1ms/step - loss: 27.1029
2/2 [==============================] - 0s 69ms/step - loss: 27.1029 - val_loss: 27.2385
Epoch 8/30
1/2 [==============>...............] - ETA: 0s - loss: 26.1831
2/2 [==============================] - 0s 922us/step - loss: 26.3147
2/2 [==============================] - 0s 67ms/step - loss: 26.3147 - val_loss: 26.4370
Epoch 9/30
1/2 [==============>...............] - ETA: 0s - loss: 25.2660
2/2 [==============================] - 0s 579us/step - loss: 25.5282
2/2 [==============================] - 0s 68ms/step - loss: 25.5282 - val_loss: 25.6456
Epoch 10/30
1/2 [==============>...............] - ETA: 0s - loss: 24.8402
2/2 [==============================] - 0s 1ms/step - loss: 24.7552
2/2 [==============================] - 0s 69ms/step - loss: 24.7552 - val_loss: 24.9117
Epoch 11/30
1/2 [==============>...............] - ETA: 0s - loss: 24.0374
2/2 [==============================] - 0s 1ms/step - loss: 24.0356
2/2 [==============================] - 0s 68ms/step - loss: 24.0356 - val_loss: 24.1890
Epoch 12/30
1/2 [==============>...............] - ETA: 0s - loss: 23.2597
2/2 [==============================] - 0s 1ms/step - loss: 23.3277
2/2 [==============================] - 0s 72ms/step - loss: 23.3277 - val_loss: 23.4832
Epoch 13/30
1/2 [==============>...............] - ETA: 0s - loss: 22.6126
2/2 [==============================] - 0s 871us/step - loss: 22.6371
2/2 [==============================] - 0s 67ms/step - loss: 22.6371 - val_loss: 22.8036
Epoch 14/30
1/2 [==============>...............] - ETA: 0s - loss: 21.8252
2/2 [==============================] - 0s 996us/step - loss: 21.9713
2/2 [==============================] - 0s 68ms/step - loss: 21.9713 - val_loss: 22.1335
Epoch 15/30
1/2 [==============>...............] - ETA: 0s - loss: 21.2576
2/2 [==============================] - 0s 998us/step - loss: 21.3161
2/2 [==============================] - 0s 67ms/step - loss: 21.3161 - val_loss: 21.4893
Epoch 16/30
1/2 [==============>...............] - ETA: 0s - loss: 20.7010
2/2 [==============================] - 0s 826us/step - loss: 20.6866
2/2 [==============================] - 0s 67ms/step - loss: 20.6866 - val_loss: 20.8711
Epoch 17/30
1/2 [==============>...............] - ETA: 0s - loss: 20.0604
2/2 [==============================] - 0s 979us/step - loss: 20.0819
2/2 [==============================] - 0s 70ms/step - loss: 20.0819 - val_loss: 20.2667
Epoch 18/30
1/2 [==============>...............] - ETA: 0s - loss: 19.5995
2/2 [==============================] - 0s 978us/step - loss: 19.4921
2/2 [==============================] - 0s 69ms/step - loss: 19.4921 - val_loss: 19.6936
Epoch 19/30
1/2 [==============>...............] - ETA: 0s - loss: 18.9969
2/2 [==============================] - 0s 1ms/step - loss: 18.9318
2/2 [==============================] - 0s 69ms/step - loss: 18.9318 - val_loss: 19.1331
Epoch 20/30
1/2 [==============>...............] - ETA: 0s - loss: 18.5862
2/2 [==============================] - 0s 899us/step - loss: 18.3851
2/2 [==============================] - 0s 67ms/step - loss: 18.3851 - val_loss: 18.5995
Epoch 21/30
1/2 [==============>...............] - ETA: 0s - loss: 18.1027
2/2 [==============================] - 0s 677us/step - loss: 17.8645
2/2 [==============================] - 0s 67ms/step - loss: 17.8645 - val_loss: 18.0868
Epoch 22/30
1/2 [==============>...............] - ETA: 0s - loss: 17.3068
2/2 [==============================] - 0s 861us/step - loss: 17.3622
2/2 [==============================] - 0s 72ms/step - loss: 17.3622 - val_loss: 17.5644
Epoch 23/30
1/2 [==============>...............] - ETA: 0s - loss: 16.7673
2/2 [==============================] - 0s 1ms/step - loss: 16.8523
2/2 [==============================] - 0s 68ms/step - loss: 16.8523 - val_loss: 17.0542
Epoch 24/30
1/2 [==============>...............] - ETA: 0s - loss: 16.5195
2/2 [==============================] - 0s 821us/step - loss: 16.3561
2/2 [==============================] - 0s 69ms/step - loss: 16.3561 - val_loss: 16.5801
Epoch 25/30
1/2 [==============>...............] - ETA: 0s - loss: 15.8990
2/2 [==============================] - 0s 1ms/step - loss: 15.8929
2/2 [==============================] - 0s 70ms/step - loss: 15.8929 - val_loss: 16.1069
Epoch 26/30
1/2 [==============>...............] - ETA: 0s - loss: 15.3819
2/2 [==============================] - 0s 1ms/step - loss: 15.4312
2/2 [==============================] - 0s 68ms/step - loss: 15.4312 - val_loss: 15.6422
Epoch 27/30
1/2 [==============>...............] - ETA: 0s - loss: 14.9736
2/2 [==============================] - 0s 801us/step - loss: 14.9786
2/2 [==============================] - 0s 66ms/step - loss: 14.9786 - val_loss: 15.1942
Epoch 28/30
1/2 [==============>...............] - ETA: 0s - loss: 14.3648
2/2 [==============================] - 0s 847us/step - loss: 14.5411
2/2 [==============================] - 0s 68ms/step - loss: 14.5411 - val_loss: 14.7441
Epoch 29/30
1/2 [==============>...............] - ETA: 0s - loss: 14.0025
2/2 [==============================] - 0s 995us/step - loss: 14.1036
2/2 [==============================] - 0s 68ms/step - loss: 14.1036 - val_loss: 14.3168
Epoch 30/30
1/2 [==============>...............] - ETA: 0s - loss: 13.8851
2/2 [==============================] - 0s 921us/step - loss: 13.6896
2/2 [==============================] - 0s 68ms/step - loss: 13.6896 - val_loss: 13.9268
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-38-46Z
Training run 3/8 (flags = list(392, 0.001, 500, 100, "relu"))
Using run directory runs/2020-11-02T19-38-51Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/100
1/1 [==============================] - 0s 12us/step - loss: 34.9205
1/1 [==============================] - 1s 579ms/step - loss: 34.9205 - val_loss: 35.2827
Epoch 2/100
1/1 [==============================] - 0s 14us/step - loss: 33.9148
1/1 [==============================] - 0s 135ms/step - loss: 33.9148 - val_loss: 34.2635
Epoch 3/100
1/1 [==============================] - 0s 13us/step - loss: 32.9303
1/1 [==============================] - 0s 139ms/step - loss: 32.9303 - val_loss: 33.2639
Epoch 4/100
1/1 [==============================] - 0s 13us/step - loss: 31.9623
1/1 [==============================] - 0s 136ms/step - loss: 31.9623 - val_loss: 32.2780
Epoch 5/100
1/1 [==============================] - 0s 14us/step - loss: 31.0049
1/1 [==============================] - 0s 137ms/step - loss: 31.0049 - val_loss: 31.2994
Epoch 6/100
1/1 [==============================] - 0s 12us/step - loss: 30.0542
1/1 [==============================] - 0s 138ms/step - loss: 30.0542 - val_loss: 30.3225
Epoch 7/100
1/1 [==============================] - 0s 16us/step - loss: 29.1058
1/1 [==============================] - 0s 137ms/step - loss: 29.1058 - val_loss: 29.3424
Epoch 8/100
1/1 [==============================] - 0s 14us/step - loss: 28.1557
1/1 [==============================] - 0s 136ms/step - loss: 28.1557 - val_loss: 28.3553
Epoch 9/100
1/1 [==============================] - 0s 11us/step - loss: 27.2002
1/1 [==============================] - 0s 134ms/step - loss: 27.2002 - val_loss: 27.3617
Epoch 10/100
1/1 [==============================] - 0s 13us/step - loss: 26.2376
1/1 [==============================] - 0s 134ms/step - loss: 26.2376 - val_loss: 26.3574
Epoch 11/100
1/1 [==============================] - 0s 14us/step - loss: 25.2647
1/1 [==============================] - 0s 133ms/step - loss: 25.2647 - val_loss: 25.3433
Epoch 12/100
1/1 [==============================] - 0s 14us/step - loss: 24.2815
1/1 [==============================] - 0s 134ms/step - loss: 24.2815 - val_loss: 24.3179
Epoch 13/100
1/1 [==============================] - 0s 13us/step - loss: 23.2888
1/1 [==============================] - 0s 141ms/step - loss: 23.2888 - val_loss: 23.2802
Epoch 14/100
1/1 [==============================] - 0s 11us/step - loss: 22.2857
1/1 [==============================] - 0s 136ms/step - loss: 22.2857 - val_loss: 22.2326
Epoch 15/100
1/1 [==============================] - 0s 14us/step - loss: 21.2740
1/1 [==============================] - 0s 135ms/step - loss: 21.2740 - val_loss: 21.1778
Epoch 16/100
1/1 [==============================] - 0s 14us/step - loss: 20.2561
1/1 [==============================] - 0s 136ms/step - loss: 20.2561 - val_loss: 20.1174
Epoch 17/100
1/1 [==============================] - 0s 14us/step - loss: 19.2331
1/1 [==============================] - 0s 138ms/step - loss: 19.2331 - val_loss: 19.0552
Epoch 18/100
1/1 [==============================] - 0s 13us/step - loss: 18.2089
1/1 [==============================] - 0s 135ms/step - loss: 18.2089 - val_loss: 17.9932
Epoch 19/100
1/1 [==============================] - 0s 13us/step - loss: 17.1855
1/1 [==============================] - 0s 135ms/step - loss: 17.1855 - val_loss: 16.9373
Epoch 20/100
1/1 [==============================] - 0s 13us/step - loss: 16.1686
1/1 [==============================] - 0s 132ms/step - loss: 16.1686 - val_loss: 15.8911
Epoch 21/100
1/1 [==============================] - 0s 13us/step - loss: 15.1626
1/1 [==============================] - 0s 132ms/step - loss: 15.1626 - val_loss: 14.8600
Epoch 22/100
1/1 [==============================] - 0s 12us/step - loss: 14.1723
1/1 [==============================] - 0s 138ms/step - loss: 14.1723 - val_loss: 13.8492
Epoch 23/100
1/1 [==============================] - 0s 13us/step - loss: 13.2032
1/1 [==============================] - 0s 136ms/step - loss: 13.2032 - val_loss: 12.8633
Epoch 24/100
1/1 [==============================] - 0s 14us/step - loss: 12.2606
1/1 [==============================] - 0s 137ms/step - loss: 12.2606 - val_loss: 11.9091
Epoch 25/100
1/1 [==============================] - 0s 14us/step - loss: 11.3506
1/1 [==============================] - 0s 134ms/step - loss: 11.3506 - val_loss: 10.9944
Epoch 26/100
1/1 [==============================] - 0s 14us/step - loss: 10.4796
1/1 [==============================] - 0s 138ms/step - loss: 10.4796 - val_loss: 10.1240
Epoch 27/100
1/1 [==============================] - 0s 15us/step - loss: 9.6530
1/1 [==============================] - 0s 133ms/step - loss: 9.6530 - val_loss: 9.3025
Epoch 28/100
1/1 [==============================] - 0s 10us/step - loss: 8.8754
1/1 [==============================] - 0s 135ms/step - loss: 8.8754 - val_loss: 8.5349
Epoch 29/100
1/1 [==============================] - 0s 11us/step - loss: 8.1509
1/1 [==============================] - 0s 145ms/step - loss: 8.1509 - val_loss: 7.8244
Epoch 30/100
1/1 [==============================] - 0s 10us/step - loss: 7.4820
1/1 [==============================] - 0s 137ms/step - loss: 7.4820 - val_loss: 7.1736
Epoch 31/100
1/1 [==============================] - 0s 14us/step - loss: 6.8710
1/1 [==============================] - 0s 136ms/step - loss: 6.8710 - val_loss: 6.5830
Epoch 32/100
1/1 [==============================] - 0s 13us/step - loss: 6.3181
1/1 [==============================] - 0s 142ms/step - loss: 6.3181 - val_loss: 6.0520
Epoch 33/100
1/1 [==============================] - 0s 15us/step - loss: 5.8231
1/1 [==============================] - 0s 134ms/step - loss: 5.8231 - val_loss: 5.5788
Epoch 34/100
1/1 [==============================] - 0s 14us/step - loss: 5.3841
1/1 [==============================] - 0s 134ms/step - loss: 5.3841 - val_loss: 5.1609
Epoch 35/100
1/1 [==============================] - 0s 11us/step - loss: 4.9985
1/1 [==============================] - 0s 137ms/step - loss: 4.9985 - val_loss: 4.7953
Epoch 36/100
1/1 [==============================] - 0s 11us/step - loss: 4.6629
1/1 [==============================] - 0s 131ms/step - loss: 4.6629 - val_loss: 4.4777
Epoch 37/100
1/1 [==============================] - 0s 11us/step - loss: 4.3730
1/1 [==============================] - 0s 134ms/step - loss: 4.3730 - val_loss: 4.2039
Epoch 38/100
1/1 [==============================] - 0s 13us/step - loss: 4.1245
1/1 [==============================] - 0s 140ms/step - loss: 4.1245 - val_loss: 3.9693
Epoch 39/100
1/1 [==============================] - 0s 12us/step - loss: 3.9129
1/1 [==============================] - 0s 134ms/step - loss: 3.9129 - val_loss: 3.7695
Epoch 40/100
1/1 [==============================] - 0s 14us/step - loss: 3.7337
1/1 [==============================] - 0s 136ms/step - loss: 3.7337 - val_loss: 3.6001
Epoch 41/100
1/1 [==============================] - 0s 13us/step - loss: 3.5824
1/1 [==============================] - 0s 133ms/step - loss: 3.5824 - val_loss: 3.4569
Epoch 42/100
1/1 [==============================] - 0s 12us/step - loss: 3.4552
1/1 [==============================] - 0s 141ms/step - loss: 3.4552 - val_loss: 3.3360
Epoch 43/100
1/1 [==============================] - 0s 13us/step - loss: 3.3482
1/1 [==============================] - 0s 137ms/step - loss: 3.3482 - val_loss: 3.2340
Epoch 44/100
1/1 [==============================] - 0s 13us/step - loss: 3.2581
1/1 [==============================] - 0s 135ms/step - loss: 3.2581 - val_loss: 3.1481
Epoch 45/100
1/1 [==============================] - 0s 12us/step - loss: 3.1821
1/1 [==============================] - 0s 132ms/step - loss: 3.1821 - val_loss: 3.0755
Epoch 46/100
1/1 [==============================] - 0s 13us/step - loss: 3.1178
1/1 [==============================] - 0s 135ms/step - loss: 3.1178 - val_loss: 3.0140
Epoch 47/100
1/1 [==============================] - 0s 14us/step - loss: 3.0628
1/1 [==============================] - 0s 134ms/step - loss: 3.0628 - val_loss: 2.9614
Epoch 48/100
1/1 [==============================] - 0s 14us/step - loss: 3.0155
1/1 [==============================] - 0s 132ms/step - loss: 3.0155 - val_loss: 2.9164
Epoch 49/100
1/1 [==============================] - 0s 11us/step - loss: 2.9745
1/1 [==============================] - 0s 135ms/step - loss: 2.9745 - val_loss: 2.8777
Epoch 50/100
1/1 [==============================] - 0s 14us/step - loss: 2.9386
1/1 [==============================] - 0s 136ms/step - loss: 2.9386 - val_loss: 2.8440
Epoch 51/100
1/1 [==============================] - 0s 15us/step - loss: 2.9067
1/1 [==============================] - 0s 144ms/step - loss: 2.9067 - val_loss: 2.8144
Epoch 52/100
1/1 [==============================] - 0s 13us/step - loss: 2.8780
1/1 [==============================] - 0s 138ms/step - loss: 2.8780 - val_loss: 2.7882
Epoch 53/100
1/1 [==============================] - 0s 14us/step - loss: 2.8520
1/1 [==============================] - 0s 137ms/step - loss: 2.8520 - val_loss: 2.7647
Epoch 54/100
1/1 [==============================] - 0s 14us/step - loss: 2.8281
1/1 [==============================] - 0s 135ms/step - loss: 2.8281 - val_loss: 2.7436
Epoch 55/100
1/1 [==============================] - 0s 14us/step - loss: 2.8060
1/1 [==============================] - 0s 133ms/step - loss: 2.8060 - val_loss: 2.7244
Epoch 56/100
1/1 [==============================] - 0s 10us/step - loss: 2.7852
1/1 [==============================] - 0s 136ms/step - loss: 2.7852 - val_loss: 2.7068
Epoch 57/100
1/1 [==============================] - 0s 11us/step - loss: 2.7656
1/1 [==============================] - 0s 134ms/step - loss: 2.7656 - val_loss: 2.6905
Epoch 58/100
1/1 [==============================] - 0s 14us/step - loss: 2.7470
1/1 [==============================] - 0s 134ms/step - loss: 2.7470 - val_loss: 2.6752
Epoch 59/100
1/1 [==============================] - 0s 24us/step - loss: 2.7291
1/1 [==============================] - 0s 135ms/step - loss: 2.7291 - val_loss: 2.6609
Epoch 60/100
1/1 [==============================] - 0s 12us/step - loss: 2.7119
1/1 [==============================] - 0s 135ms/step - loss: 2.7119 - val_loss: 2.6473
Epoch 61/100
1/1 [==============================] - 0s 14us/step - loss: 2.6953
1/1 [==============================] - 0s 141ms/step - loss: 2.6953 - val_loss: 2.6344
Epoch 62/100
1/1 [==============================] - 0s 14us/step - loss: 2.6792
1/1 [==============================] - 0s 133ms/step - loss: 2.6792 - val_loss: 2.6220
Epoch 63/100
1/1 [==============================] - 0s 10us/step - loss: 2.6636
1/1 [==============================] - 0s 134ms/step - loss: 2.6636 - val_loss: 2.6101
Epoch 64/100
1/1 [==============================] - 0s 11us/step - loss: 2.6483
1/1 [==============================] - 0s 133ms/step - loss: 2.6483 - val_loss: 2.5987
Epoch 65/100
1/1 [==============================] - 0s 11us/step - loss: 2.6334
1/1 [==============================] - 0s 133ms/step - loss: 2.6334 - val_loss: 2.5875
Epoch 66/100
1/1 [==============================] - 0s 11us/step - loss: 2.6188
1/1 [==============================] - 0s 136ms/step - loss: 2.6188 - val_loss: 2.5767
Epoch 67/100
1/1 [==============================] - 0s 14us/step - loss: 2.6045
1/1 [==============================] - 0s 134ms/step - loss: 2.6045 - val_loss: 2.5661
Epoch 68/100
1/1 [==============================] - 0s 13us/step - loss: 2.5904
1/1 [==============================] - 0s 137ms/step - loss: 2.5904 - val_loss: 2.5558
Epoch 69/100
1/1 [==============================] - 0s 12us/step - loss: 2.5766
1/1 [==============================] - 0s 134ms/step - loss: 2.5766 - val_loss: 2.5457
Epoch 70/100
1/1 [==============================] - 0s 13us/step - loss: 2.5629
1/1 [==============================] - 0s 133ms/step - loss: 2.5629 - val_loss: 2.5359
Epoch 71/100
1/1 [==============================] - 0s 11us/step - loss: 2.5495
1/1 [==============================] - 0s 139ms/step - loss: 2.5495 - val_loss: 2.5261
Epoch 72/100
1/1 [==============================] - 0s 14us/step - loss: 2.5363
1/1 [==============================] - 0s 135ms/step - loss: 2.5363 - val_loss: 2.5166
Epoch 73/100
1/1 [==============================] - 0s 11us/step - loss: 2.5233
1/1 [==============================] - 0s 134ms/step - loss: 2.5233 - val_loss: 2.5072
Epoch 74/100
1/1 [==============================] - 0s 15us/step - loss: 2.5105
1/1 [==============================] - 0s 133ms/step - loss: 2.5105 - val_loss: 2.4978
Epoch 75/100
1/1 [==============================] - 0s 13us/step - loss: 2.4979
1/1 [==============================] - 0s 134ms/step - loss: 2.4979 - val_loss: 2.4886
Epoch 76/100
1/1 [==============================] - 0s 13us/step - loss: 2.4854
1/1 [==============================] - 0s 134ms/step - loss: 2.4854 - val_loss: 2.4795
Epoch 77/100
1/1 [==============================] - 0s 15us/step - loss: 2.4731
1/1 [==============================] - 0s 134ms/step - loss: 2.4731 - val_loss: 2.4705
Epoch 78/100
1/1 [==============================] - 0s 12us/step - loss: 2.4610
1/1 [==============================] - 0s 133ms/step - loss: 2.4610 - val_loss: 2.4615
Epoch 79/100
1/1 [==============================] - 0s 14us/step - loss: 2.4490
1/1 [==============================] - 0s 133ms/step - loss: 2.4490 - val_loss: 2.4527
Epoch 80/100
1/1 [==============================] - 0s 11us/step - loss: 2.4371
1/1 [==============================] - 0s 141ms/step - loss: 2.4371 - val_loss: 2.4440
Epoch 81/100
1/1 [==============================] - 0s 14us/step - loss: 2.4253
1/1 [==============================] - 0s 133ms/step - loss: 2.4253 - val_loss: 2.4353
Epoch 82/100
1/1 [==============================] - 0s 13us/step - loss: 2.4137
1/1 [==============================] - 0s 132ms/step - loss: 2.4137 - val_loss: 2.4266
Epoch 83/100
1/1 [==============================] - 0s 15us/step - loss: 2.4022
1/1 [==============================] - 0s 137ms/step - loss: 2.4022 - val_loss: 2.4181
Epoch 84/100
1/1 [==============================] - 0s 14us/step - loss: 2.3909
1/1 [==============================] - 0s 135ms/step - loss: 2.3909 - val_loss: 2.4096
Epoch 85/100
1/1 [==============================] - 0s 14us/step - loss: 2.3796
1/1 [==============================] - 0s 133ms/step - loss: 2.3796 - val_loss: 2.4012
Epoch 86/100
1/1 [==============================] - 0s 13us/step - loss: 2.3685
1/1 [==============================] - 0s 134ms/step - loss: 2.3685 - val_loss: 2.3929
Epoch 87/100
1/1 [==============================] - 0s 14us/step - loss: 2.3576
1/1 [==============================] - 0s 133ms/step - loss: 2.3576 - val_loss: 2.3846
Epoch 88/100
1/1 [==============================] - 0s 14us/step - loss: 2.3467
1/1 [==============================] - 0s 135ms/step - loss: 2.3467 - val_loss: 2.3763
Epoch 89/100
1/1 [==============================] - 0s 13us/step - loss: 2.3360
1/1 [==============================] - 0s 132ms/step - loss: 2.3360 - val_loss: 2.3681
Epoch 90/100
1/1 [==============================] - 0s 14us/step - loss: 2.3254
1/1 [==============================] - 0s 143ms/step - loss: 2.3254 - val_loss: 2.3599
Epoch 91/100
1/1 [==============================] - 0s 14us/step - loss: 2.3149
1/1 [==============================] - 0s 135ms/step - loss: 2.3149 - val_loss: 2.3517
Epoch 92/100
1/1 [==============================] - 0s 12us/step - loss: 2.3044
1/1 [==============================] - 0s 135ms/step - loss: 2.3044 - val_loss: 2.3436
Epoch 93/100
1/1 [==============================] - 0s 13us/step - loss: 2.2941
1/1 [==============================] - 0s 132ms/step - loss: 2.2941 - val_loss: 2.3355
Epoch 94/100
1/1 [==============================] - 0s 10us/step - loss: 2.2838
1/1 [==============================] - 0s 136ms/step - loss: 2.2838 - val_loss: 2.3274
Epoch 95/100
1/1 [==============================] - 0s 14us/step - loss: 2.2737
1/1 [==============================] - 0s 136ms/step - loss: 2.2737 - val_loss: 2.3193
Epoch 96/100
1/1 [==============================] - 0s 14us/step - loss: 2.2636
1/1 [==============================] - 0s 135ms/step - loss: 2.2636 - val_loss: 2.3113
Epoch 97/100
1/1 [==============================] - 0s 14us/step - loss: 2.2536
1/1 [==============================] - 0s 135ms/step - loss: 2.2536 - val_loss: 2.3034
Epoch 98/100
1/1 [==============================] - 0s 14us/step - loss: 2.2437
1/1 [==============================] - 0s 134ms/step - loss: 2.2437 - val_loss: 2.2954
Epoch 99/100
1/1 [==============================] - 0s 14us/step - loss: 2.2338
1/1 [==============================] - 0s 134ms/step - loss: 2.2338 - val_loss: 2.2876
Epoch 100/100
1/1 [==============================] - 0s 13us/step - loss: 2.2241
1/1 [==============================] - 0s 143ms/step - loss: 2.2241 - val_loss: 2.2797
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-38-51Z
Training run 4/8 (flags = list(64, 1e-04, 500, 100, "tanh"))
Using run directory runs/2020-11-02T19-39-06Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/100
1/1 [==============================] - 0s 11us/step - loss: 35.9695
1/1 [==============================] - 1s 581ms/step - loss: 35.9695 - val_loss: 35.6071
Epoch 2/100
1/1 [==============================] - 0s 16us/step - loss: 35.8771
1/1 [==============================] - 0s 137ms/step - loss: 35.8771 - val_loss: 35.5215
Epoch 3/100
1/1 [==============================] - 0s 10us/step - loss: 35.7850
1/1 [==============================] - 0s 134ms/step - loss: 35.7850 - val_loss: 35.4362
Epoch 4/100
1/1 [==============================] - 0s 15us/step - loss: 35.6931
1/1 [==============================] - 0s 137ms/step - loss: 35.6931 - val_loss: 35.3511
Epoch 5/100
1/1 [==============================] - 0s 13us/step - loss: 35.6016
1/1 [==============================] - 0s 137ms/step - loss: 35.6016 - val_loss: 35.2662
Epoch 6/100
1/1 [==============================] - 0s 42us/step - loss: 35.5102
1/1 [==============================] - 0s 138ms/step - loss: 35.5102 - val_loss: 35.1815
Epoch 7/100
1/1 [==============================] - 0s 10us/step - loss: 35.4191
1/1 [==============================] - 0s 134ms/step - loss: 35.4191 - val_loss: 35.0970
Epoch 8/100
1/1 [==============================] - 0s 17us/step - loss: 35.3283
1/1 [==============================] - 0s 138ms/step - loss: 35.3283 - val_loss: 35.0127
Epoch 9/100
1/1 [==============================] - 0s 13us/step - loss: 35.2377
1/1 [==============================] - 0s 133ms/step - loss: 35.2377 - val_loss: 34.9286
Epoch 10/100
1/1 [==============================] - 0s 11us/step - loss: 35.1474
1/1 [==============================] - 0s 132ms/step - loss: 35.1474 - val_loss: 34.8447
Epoch 11/100
1/1 [==============================] - 0s 13us/step - loss: 35.0573
1/1 [==============================] - 0s 140ms/step - loss: 35.0573 - val_loss: 34.7610
Epoch 12/100
1/1 [==============================] - 0s 25us/step - loss: 34.9674
1/1 [==============================] - 0s 131ms/step - loss: 34.9674 - val_loss: 34.6775
Epoch 13/100
1/1 [==============================] - 0s 22us/step - loss: 34.8778
1/1 [==============================] - 0s 133ms/step - loss: 34.8778 - val_loss: 34.5942
Epoch 14/100
1/1 [==============================] - 0s 10us/step - loss: 34.7883
1/1 [==============================] - 0s 136ms/step - loss: 34.7883 - val_loss: 34.5111
Epoch 15/100
1/1 [==============================] - 0s 16us/step - loss: 34.6991
1/1 [==============================] - 0s 145ms/step - loss: 34.6991 - val_loss: 34.4281
Epoch 16/100
1/1 [==============================] - 0s 10us/step - loss: 34.6102
1/1 [==============================] - 0s 138ms/step - loss: 34.6102 - val_loss: 34.3453
Epoch 17/100
1/1 [==============================] - 0s 16us/step - loss: 34.5214
1/1 [==============================] - 0s 136ms/step - loss: 34.5214 - val_loss: 34.2627
Epoch 18/100
1/1 [==============================] - 0s 15us/step - loss: 34.4329
1/1 [==============================] - 0s 135ms/step - loss: 34.4329 - val_loss: 34.1803
Epoch 19/100
1/1 [==============================] - 0s 12us/step - loss: 34.3446
1/1 [==============================] - 0s 133ms/step - loss: 34.3446 - val_loss: 34.0981
Epoch 20/100
1/1 [==============================] - 0s 16us/step - loss: 34.2564
1/1 [==============================] - 0s 133ms/step - loss: 34.2564 - val_loss: 34.0160
Epoch 21/100
1/1 [==============================] - 0s 10us/step - loss: 34.1685
1/1 [==============================] - 0s 143ms/step - loss: 34.1685 - val_loss: 33.9341
Epoch 22/100
1/1 [==============================] - 0s 19us/step - loss: 34.0808
1/1 [==============================] - 0s 136ms/step - loss: 34.0808 - val_loss: 33.8524
Epoch 23/100
1/1 [==============================] - 0s 12us/step - loss: 33.9933
1/1 [==============================] - 0s 135ms/step - loss: 33.9933 - val_loss: 33.7708
Epoch 24/100
1/1 [==============================] - 0s 15us/step - loss: 33.9060
1/1 [==============================] - 0s 137ms/step - loss: 33.9060 - val_loss: 33.6893
Epoch 25/100
1/1 [==============================] - 0s 15us/step - loss: 33.8189
1/1 [==============================] - 0s 135ms/step - loss: 33.8189 - val_loss: 33.6081
Epoch 26/100
1/1 [==============================] - 0s 15us/step - loss: 33.7320
1/1 [==============================] - 0s 134ms/step - loss: 33.7320 - val_loss: 33.5270
Epoch 27/100
1/1 [==============================] - 0s 13us/step - loss: 33.6453
1/1 [==============================] - 0s 136ms/step - loss: 33.6453 - val_loss: 33.4460
Epoch 28/100
1/1 [==============================] - 0s 16us/step - loss: 33.5587
1/1 [==============================] - 0s 134ms/step - loss: 33.5587 - val_loss: 33.3652
Epoch 29/100
1/1 [==============================] - 0s 11us/step - loss: 33.4723
1/1 [==============================] - 0s 136ms/step - loss: 33.4723 - val_loss: 33.2845
Epoch 30/100
1/1 [==============================] - 0s 12us/step - loss: 33.3862
1/1 [==============================] - 0s 140ms/step - loss: 33.3862 - val_loss: 33.2040
Epoch 31/100
1/1 [==============================] - 0s 15us/step - loss: 33.3002
1/1 [==============================] - 0s 136ms/step - loss: 33.3002 - val_loss: 33.1236
Epoch 32/100
1/1 [==============================] - 0s 16us/step - loss: 33.2143
1/1 [==============================] - 0s 136ms/step - loss: 33.2143 - val_loss: 33.0434
Epoch 33/100
1/1 [==============================] - 0s 16us/step - loss: 33.1287
1/1 [==============================] - 0s 134ms/step - loss: 33.1287 - val_loss: 32.9633
Epoch 34/100
1/1 [==============================] - 0s 12us/step - loss: 33.0432
1/1 [==============================] - 0s 136ms/step - loss: 33.0432 - val_loss: 32.8833
Epoch 35/100
1/1 [==============================] - 0s 21us/step - loss: 32.9579
1/1 [==============================] - 0s 137ms/step - loss: 32.9579 - val_loss: 32.8035
Epoch 36/100
1/1 [==============================] - 0s 13us/step - loss: 32.8727
1/1 [==============================] - 0s 135ms/step - loss: 32.8727 - val_loss: 32.7237
Epoch 37/100
1/1 [==============================] - 0s 15us/step - loss: 32.7878
1/1 [==============================] - 0s 136ms/step - loss: 32.7878 - val_loss: 32.6442
Epoch 38/100
1/1 [==============================] - 0s 15us/step - loss: 32.7029
1/1 [==============================] - 0s 134ms/step - loss: 32.7029 - val_loss: 32.5647
Epoch 39/100
1/1 [==============================] - 0s 18us/step - loss: 32.6183
1/1 [==============================] - 0s 135ms/step - loss: 32.6183 - val_loss: 32.4854
Epoch 40/100
1/1 [==============================] - 0s 12us/step - loss: 32.5338
1/1 [==============================] - 0s 140ms/step - loss: 32.5338 - val_loss: 32.4062
Epoch 41/100
1/1 [==============================] - 0s 15us/step - loss: 32.4494
1/1 [==============================] - 0s 137ms/step - loss: 32.4494 - val_loss: 32.3271
Epoch 42/100
1/1 [==============================] - 0s 16us/step - loss: 32.3652
1/1 [==============================] - 0s 134ms/step - loss: 32.3652 - val_loss: 32.2481
Epoch 43/100
1/1 [==============================] - 0s 10us/step - loss: 32.2812
1/1 [==============================] - 0s 136ms/step - loss: 32.2812 - val_loss: 32.1693
Epoch 44/100
1/1 [==============================] - 0s 15us/step - loss: 32.1973
1/1 [==============================] - 0s 133ms/step - loss: 32.1973 - val_loss: 32.0905
Epoch 45/100
1/1 [==============================] - 0s 11us/step - loss: 32.1135
1/1 [==============================] - 0s 133ms/step - loss: 32.1135 - val_loss: 32.0119
Epoch 46/100
1/1 [==============================] - 0s 15us/step - loss: 32.0299
1/1 [==============================] - 0s 134ms/step - loss: 32.0299 - val_loss: 31.9334
Epoch 47/100
1/1 [==============================] - 0s 26us/step - loss: 31.9464
1/1 [==============================] - 0s 139ms/step - loss: 31.9464 - val_loss: 31.8550
Epoch 48/100
1/1 [==============================] - 0s 23us/step - loss: 31.8631
1/1 [==============================] - 0s 137ms/step - loss: 31.8631 - val_loss: 31.7767
Epoch 49/100
1/1 [==============================] - 0s 21us/step - loss: 31.7799
1/1 [==============================] - 0s 132ms/step - loss: 31.7799 - val_loss: 31.6985
Epoch 50/100
1/1 [==============================] - 0s 11us/step - loss: 31.6969
1/1 [==============================] - 0s 146ms/step - loss: 31.6969 - val_loss: 31.6204
Epoch 51/100
1/1 [==============================] - 0s 11us/step - loss: 31.6139
1/1 [==============================] - 0s 133ms/step - loss: 31.6139 - val_loss: 31.5424
Epoch 52/100
1/1 [==============================] - 0s 13us/step - loss: 31.5311
1/1 [==============================] - 0s 134ms/step - loss: 31.5311 - val_loss: 31.4646
Epoch 53/100
1/1 [==============================] - 0s 14us/step - loss: 31.4485
1/1 [==============================] - 0s 135ms/step - loss: 31.4485 - val_loss: 31.3868
Epoch 54/100
1/1 [==============================] - 0s 15us/step - loss: 31.3659
1/1 [==============================] - 0s 136ms/step - loss: 31.3659 - val_loss: 31.3091
Epoch 55/100
1/1 [==============================] - 0s 12us/step - loss: 31.2835
1/1 [==============================] - 0s 134ms/step - loss: 31.2835 - val_loss: 31.2315
Epoch 56/100
1/1 [==============================] - 0s 26us/step - loss: 31.2012
1/1 [==============================] - 0s 134ms/step - loss: 31.2012 - val_loss: 31.1540
Epoch 57/100
1/1 [==============================] - 0s 9us/step - loss: 31.1191
1/1 [==============================] - 0s 133ms/step - loss: 31.1191 - val_loss: 31.0766
Epoch 58/100
1/1 [==============================] - 0s 15us/step - loss: 31.0370
1/1 [==============================] - 0s 133ms/step - loss: 31.0370 - val_loss: 30.9992
Epoch 59/100
1/1 [==============================] - 0s 13us/step - loss: 30.9551
1/1 [==============================] - 0s 138ms/step - loss: 30.9551 - val_loss: 30.9220
Epoch 60/100
1/1 [==============================] - 0s 10us/step - loss: 30.8733
1/1 [==============================] - 0s 134ms/step - loss: 30.8733 - val_loss: 30.8448
Epoch 61/100
1/1 [==============================] - 0s 20us/step - loss: 30.7916
1/1 [==============================] - 0s 137ms/step - loss: 30.7916 - val_loss: 30.7678
Epoch 62/100
1/1 [==============================] - 0s 14us/step - loss: 30.7100
1/1 [==============================] - 0s 134ms/step - loss: 30.7100 - val_loss: 30.6908
Epoch 63/100
1/1 [==============================] - 0s 13us/step - loss: 30.6285
1/1 [==============================] - 0s 133ms/step - loss: 30.6285 - val_loss: 30.6139
Epoch 64/100
1/1 [==============================] - 0s 16us/step - loss: 30.5472
1/1 [==============================] - 0s 133ms/step - loss: 30.5472 - val_loss: 30.5371
Epoch 65/100
1/1 [==============================] - 0s 10us/step - loss: 30.4659
1/1 [==============================] - 0s 134ms/step - loss: 30.4659 - val_loss: 30.4603
Epoch 66/100
1/1 [==============================] - 0s 14us/step - loss: 30.3848
1/1 [==============================] - 0s 136ms/step - loss: 30.3848 - val_loss: 30.3837
Epoch 67/100
1/1 [==============================] - 0s 14us/step - loss: 30.3037
1/1 [==============================] - 0s 134ms/step - loss: 30.3037 - val_loss: 30.3071
Epoch 68/100
1/1 [==============================] - 0s 33us/step - loss: 30.2228
1/1 [==============================] - 0s 133ms/step - loss: 30.2228 - val_loss: 30.2306
Epoch 69/100
1/1 [==============================] - 0s 10us/step - loss: 30.1419
1/1 [==============================] - 0s 140ms/step - loss: 30.1419 - val_loss: 30.1541
Epoch 70/100
1/1 [==============================] - 0s 15us/step - loss: 30.0612
1/1 [==============================] - 0s 136ms/step - loss: 30.0612 - val_loss: 30.0778
Epoch 71/100
1/1 [==============================] - 0s 16us/step - loss: 29.9806
1/1 [==============================] - 0s 133ms/step - loss: 29.9806 - val_loss: 30.0015
Epoch 72/100
1/1 [==============================] - 0s 13us/step - loss: 29.9000
1/1 [==============================] - 0s 134ms/step - loss: 29.9000 - val_loss: 29.9252
Epoch 73/100
1/1 [==============================] - 0s 16us/step - loss: 29.8196
1/1 [==============================] - 0s 138ms/step - loss: 29.8196 - val_loss: 29.8491
Epoch 74/100
1/1 [==============================] - 0s 16us/step - loss: 29.7392
1/1 [==============================] - 0s 142ms/step - loss: 29.7392 - val_loss: 29.7730
Epoch 75/100
1/1 [==============================] - 0s 15us/step - loss: 29.6589
1/1 [==============================] - 0s 135ms/step - loss: 29.6589 - val_loss: 29.6970
Epoch 76/100
1/1 [==============================] - 0s 17us/step - loss: 29.5788
1/1 [==============================] - 0s 136ms/step - loss: 29.5788 - val_loss: 29.6210
Epoch 77/100
1/1 [==============================] - 0s 15us/step - loss: 29.4987
1/1 [==============================] - 0s 133ms/step - loss: 29.4987 - val_loss: 29.5451
Epoch 78/100
1/1 [==============================] - 0s 15us/step - loss: 29.4187
1/1 [==============================] - 0s 132ms/step - loss: 29.4187 - val_loss: 29.4693
Epoch 79/100
1/1 [==============================] - 0s 10us/step - loss: 29.3388
1/1 [==============================] - 0s 144ms/step - loss: 29.3388 - val_loss: 29.3935
Epoch 80/100
1/1 [==============================] - 0s 17us/step - loss: 29.2590
1/1 [==============================] - 0s 137ms/step - loss: 29.2590 - val_loss: 29.3178
Epoch 81/100
1/1 [==============================] - 0s 15us/step - loss: 29.1792
1/1 [==============================] - 0s 137ms/step - loss: 29.1792 - val_loss: 29.2421
Epoch 82/100
1/1 [==============================] - 0s 16us/step - loss: 29.0996
1/1 [==============================] - 0s 137ms/step - loss: 29.0996 - val_loss: 29.1665
Epoch 83/100
1/1 [==============================] - 0s 16us/step - loss: 29.0200
1/1 [==============================] - 0s 137ms/step - loss: 29.0200 - val_loss: 29.0910
Epoch 84/100
1/1 [==============================] - 0s 16us/step - loss: 28.9405
1/1 [==============================] - 0s 135ms/step - loss: 28.9405 - val_loss: 29.0155
Epoch 85/100
1/1 [==============================] - 0s 16us/step - loss: 28.8611
1/1 [==============================] - 0s 133ms/step - loss: 28.8611 - val_loss: 28.9401
Epoch 86/100
1/1 [==============================] - 0s 10us/step - loss: 28.7818
1/1 [==============================] - 0s 136ms/step - loss: 28.7818 - val_loss: 28.8647
Epoch 87/100
1/1 [==============================] - 0s 17us/step - loss: 28.7026
1/1 [==============================] - 0s 137ms/step - loss: 28.7026 - val_loss: 28.7894
Epoch 88/100
1/1 [==============================] - 0s 45us/step - loss: 28.6234
1/1 [==============================] - 0s 143ms/step - loss: 28.6234 - val_loss: 28.7141
Epoch 89/100
1/1 [==============================] - 0s 16us/step - loss: 28.5443
1/1 [==============================] - 0s 137ms/step - loss: 28.5443 - val_loss: 28.6389
Epoch 90/100
1/1 [==============================] - 0s 16us/step - loss: 28.4653
1/1 [==============================] - 0s 135ms/step - loss: 28.4653 - val_loss: 28.5637
Epoch 91/100
1/1 [==============================] - 0s 16us/step - loss: 28.3863
1/1 [==============================] - 0s 135ms/step - loss: 28.3863 - val_loss: 28.4886
Epoch 92/100
1/1 [==============================] - 0s 17us/step - loss: 28.3074
1/1 [==============================] - 0s 133ms/step - loss: 28.3074 - val_loss: 28.4135
Epoch 93/100
1/1 [==============================] - 0s 10us/step - loss: 28.2286
1/1 [==============================] - 0s 132ms/step - loss: 28.2286 - val_loss: 28.3385
Epoch 94/100
1/1 [==============================] - 0s 11us/step - loss: 28.1499
1/1 [==============================] - 0s 134ms/step - loss: 28.1499 - val_loss: 28.2635
Epoch 95/100
1/1 [==============================] - 0s 15us/step - loss: 28.0712
1/1 [==============================] - 0s 137ms/step - loss: 28.0712 - val_loss: 28.1885
Epoch 96/100
1/1 [==============================] - 0s 14us/step - loss: 27.9926
1/1 [==============================] - 0s 135ms/step - loss: 27.9926 - val_loss: 28.1136
Epoch 97/100
1/1 [==============================] - 0s 16us/step - loss: 27.9141
1/1 [==============================] - 0s 135ms/step - loss: 27.9141 - val_loss: 28.0388
Epoch 98/100
1/1 [==============================] - 0s 14us/step - loss: 27.8356
1/1 [==============================] - 0s 137ms/step - loss: 27.8356 - val_loss: 27.9640
Epoch 99/100
1/1 [==============================] - 0s 15us/step - loss: 27.7572
1/1 [==============================] - 0s 135ms/step - loss: 27.7572 - val_loss: 27.8892
Epoch 100/100
1/1 [==============================] - 0s 15us/step - loss: 27.6789
1/1 [==============================] - 0s 135ms/step - loss: 27.6789 - val_loss: 27.8145
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-39-06Z
Training run 5/8 (flags = list(128, 1e-04, 100, 30, "tanh"))
Using run directory runs/2020-11-02T19-39-21Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/30
1/3 [=========>....................] - ETA: 0s - loss: 36.4107
3/3 [==============================] - 0s 999us/step - loss: 36.3974
3/3 [==============================] - 1s 199ms/step - loss: 36.3974 - val_loss: 35.6196
Epoch 2/30
1/3 [=========>....................] - ETA: 0s - loss: 36.9115
3/3 [==============================] - 0s 1ms/step - loss: 36.1262
3/3 [==============================] - 0s 48ms/step - loss: 36.1262 - val_loss: 35.3767
Epoch 3/30
1/3 [=========>....................] - ETA: 0s - loss: 35.8315
3/3 [==============================] - 0s 1ms/step - loss: 35.8532
3/3 [==============================] - 0s 46ms/step - loss: 35.8532 - val_loss: 35.1307
Epoch 4/30
1/3 [=========>....................] - ETA: 0s - loss: 35.5317
3/3 [==============================] - 0s 1ms/step - loss: 35.5815
3/3 [==============================] - 0s 47ms/step - loss: 35.5815 - val_loss: 34.9101
Epoch 5/30
1/3 [=========>....................] - ETA: 0s - loss: 34.7389
3/3 [==============================] - 0s 1ms/step - loss: 35.3183
3/3 [==============================] - 0s 48ms/step - loss: 35.3183 - val_loss: 34.6800
Epoch 6/30
1/3 [=========>....................] - ETA: 0s - loss: 36.0036
3/3 [==============================] - 0s 1ms/step - loss: 35.0704
3/3 [==============================] - 0s 46ms/step - loss: 35.0704 - val_loss: 34.4620
Epoch 7/30
1/3 [=========>....................] - ETA: 0s - loss: 34.1088
3/3 [==============================] - 0s 1ms/step - loss: 34.8066
3/3 [==============================] - 0s 46ms/step - loss: 34.8066 - val_loss: 34.2507
Epoch 8/30
1/3 [=========>....................] - ETA: 0s - loss: 35.5251
3/3 [==============================] - 0s 1ms/step - loss: 34.5452
3/3 [==============================] - 0s 46ms/step - loss: 34.5452 - val_loss: 34.0522
Epoch 9/30
1/3 [=========>....................] - ETA: 0s - loss: 34.8235
3/3 [==============================] - 0s 1ms/step - loss: 34.2870
3/3 [==============================] - 0s 47ms/step - loss: 34.2870 - val_loss: 33.8415
Epoch 10/30
1/3 [=========>....................] - ETA: 0s - loss: 32.9989
3/3 [==============================] - 0s 1ms/step - loss: 34.0380
3/3 [==============================] - 0s 45ms/step - loss: 34.0380 - val_loss: 33.6215
Epoch 11/30
1/3 [=========>....................] - ETA: 0s - loss: 32.0274
3/3 [==============================] - 0s 911us/step - loss: 33.7748
3/3 [==============================] - 0s 45ms/step - loss: 33.7748 - val_loss: 33.4119
Epoch 12/30
1/3 [=========>....................] - ETA: 0s - loss: 34.3070
3/3 [==============================] - 0s 1ms/step - loss: 33.5200
3/3 [==============================] - 0s 45ms/step - loss: 33.5200 - val_loss: 33.1926
Epoch 13/30
1/3 [=========>....................] - ETA: 0s - loss: 33.1277
3/3 [==============================] - 0s 1ms/step - loss: 33.2639
3/3 [==============================] - 0s 45ms/step - loss: 33.2639 - val_loss: 32.9949
Epoch 14/30
1/3 [=========>....................] - ETA: 0s - loss: 33.3654
3/3 [==============================] - 0s 1ms/step - loss: 33.0066
3/3 [==============================] - 0s 46ms/step - loss: 33.0066 - val_loss: 32.7898
Epoch 15/30
1/3 [=========>....................] - ETA: 0s - loss: 32.7411
3/3 [==============================] - 0s 1ms/step - loss: 32.7479
3/3 [==============================] - 0s 45ms/step - loss: 32.7479 - val_loss: 32.5735
Epoch 16/30
1/3 [=========>....................] - ETA: 0s - loss: 31.1908
3/3 [==============================] - 0s 1ms/step - loss: 32.5124
3/3 [==============================] - 0s 46ms/step - loss: 32.5124 - val_loss: 32.3716
Epoch 17/30
1/3 [=========>....................] - ETA: 0s - loss: 32.1822
3/3 [==============================] - 0s 1ms/step - loss: 32.2562
3/3 [==============================] - 0s 46ms/step - loss: 32.2562 - val_loss: 32.1707
Epoch 18/30
1/3 [=========>....................] - ETA: 0s - loss: 30.7002
3/3 [==============================] - 0s 1ms/step - loss: 32.0130
3/3 [==============================] - 0s 45ms/step - loss: 32.0130 - val_loss: 31.9694
Epoch 19/30
1/3 [=========>....................] - ETA: 0s - loss: 32.2222
3/3 [==============================] - 0s 1ms/step - loss: 31.7801
3/3 [==============================] - 0s 48ms/step - loss: 31.7801 - val_loss: 31.7613
Epoch 20/30
1/3 [=========>....................] - ETA: 0s - loss: 32.1743
3/3 [==============================] - 0s 1ms/step - loss: 31.5454
3/3 [==============================] - 0s 46ms/step - loss: 31.5454 - val_loss: 31.5422
Epoch 21/30
1/3 [=========>....................] - ETA: 0s - loss: 31.7503
3/3 [==============================] - 0s 1ms/step - loss: 31.2986
3/3 [==============================] - 0s 46ms/step - loss: 31.2986 - val_loss: 31.3280
Epoch 22/30
1/3 [=========>....................] - ETA: 0s - loss: 30.4608
3/3 [==============================] - 0s 1ms/step - loss: 31.0572
3/3 [==============================] - 0s 47ms/step - loss: 31.0572 - val_loss: 31.1152
Epoch 23/30
1/3 [=========>....................] - ETA: 0s - loss: 30.2903
3/3 [==============================] - 0s 1ms/step - loss: 30.8076
3/3 [==============================] - 0s 46ms/step - loss: 30.8076 - val_loss: 30.9019
Epoch 24/30
1/3 [=========>....................] - ETA: 0s - loss: 31.0547
3/3 [==============================] - 0s 1ms/step - loss: 30.5730
3/3 [==============================] - 0s 47ms/step - loss: 30.5730 - val_loss: 30.6832
Epoch 25/30
1/3 [=========>....................] - ETA: 0s - loss: 30.4960
3/3 [==============================] - 0s 1ms/step - loss: 30.3355
3/3 [==============================] - 0s 45ms/step - loss: 30.3355 - val_loss: 30.4809
Epoch 26/30
1/3 [=========>....................] - ETA: 0s - loss: 30.0551
3/3 [==============================] - 0s 1ms/step - loss: 30.1010
3/3 [==============================] - 0s 46ms/step - loss: 30.1010 - val_loss: 30.2820
Epoch 27/30
1/3 [=========>....................] - ETA: 0s - loss: 29.5303
3/3 [==============================] - 0s 1ms/step - loss: 29.8735
3/3 [==============================] - 0s 45ms/step - loss: 29.8735 - val_loss: 30.0693
Epoch 28/30
1/3 [=========>....................] - ETA: 0s - loss: 30.3087
3/3 [==============================] - 0s 997us/step - loss: 29.6421
3/3 [==============================] - 0s 46ms/step - loss: 29.6421 - val_loss: 29.8475
Epoch 29/30
1/3 [=========>....................] - ETA: 0s - loss: 28.4288
3/3 [==============================] - 0s 1ms/step - loss: 29.4046
3/3 [==============================] - 0s 47ms/step - loss: 29.4046 - val_loss: 29.6481
Epoch 30/30
1/3 [=========>....................] - ETA: 0s - loss: 29.6374
3/3 [==============================] - 0s 1ms/step - loss: 29.1717
3/3 [==============================] - 0s 47ms/step - loss: 29.1717 - val_loss: 29.4434
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-39-21Z
Training run 6/8 (flags = list(392, 0.05, 500, 100, "sigmoid"))
Using run directory runs/2020-11-02T19-39-26Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/100
1/1 [==============================] - 0s 11us/step - loss: 38.5676
1/1 [==============================] - 1s 692ms/step - loss: 38.5676 - val_loss: 4415.9268
Epoch 2/100
1/1 [==============================] - 0s 12us/step - loss: 4428.5933
1/1 [==============================] - 0s 137ms/step - loss: 4428.5933 - val_loss: 151.3512
Epoch 3/100
1/1 [==============================] - 0s 13us/step - loss: 149.1063
1/1 [==============================] - 0s 134ms/step - loss: 149.1063 - val_loss: 118.9645
Epoch 4/100
1/1 [==============================] - 0s 15us/step - loss: 116.9800
1/1 [==============================] - 0s 149ms/step - loss: 116.9800 - val_loss: 96.6139
Epoch 5/100
1/1 [==============================] - 0s 14us/step - loss: 94.8349
1/1 [==============================] - 0s 137ms/step - loss: 94.8349 - val_loss: 78.5241
Epoch 6/100
1/1 [==============================] - 0s 11us/step - loss: 76.9299
1/1 [==============================] - 0s 134ms/step - loss: 76.9299 - val_loss: 63.8693
Epoch 7/100
1/1 [==============================] - 0s 11us/step - loss: 62.4413
1/1 [==============================] - 0s 136ms/step - loss: 62.4413 - val_loss: 51.9917
Epoch 8/100
1/1 [==============================] - 0s 12us/step - loss: 50.7133
1/1 [==============================] - 0s 136ms/step - loss: 50.7133 - val_loss: 42.3621
Epoch 9/100
1/1 [==============================] - 0s 13us/step - loss: 41.2182
1/1 [==============================] - 0s 134ms/step - loss: 41.2182 - val_loss: 34.5530
Epoch 10/100
1/1 [==============================] - 0s 11us/step - loss: 33.5301
1/1 [==============================] - 0s 143ms/step - loss: 33.5301 - val_loss: 28.2186
Epoch 11/100
1/1 [==============================] - 0s 14us/step - loss: 27.3046
1/1 [==============================] - 0s 136ms/step - loss: 27.3046 - val_loss: 23.0793
Epoch 12/100
1/1 [==============================] - 0s 14us/step - loss: 22.2634
1/1 [==============================] - 0s 135ms/step - loss: 22.2634 - val_loss: 18.9086
Epoch 13/100
1/1 [==============================] - 0s 14us/step - loss: 18.1809
1/1 [==============================] - 0s 133ms/step - loss: 18.1809 - val_loss: 15.5231
Epoch 14/100
1/1 [==============================] - 0s 11us/step - loss: 14.8747
1/1 [==============================] - 0s 139ms/step - loss: 14.8747 - val_loss: 12.7742
Epoch 15/100
1/1 [==============================] - 0s 14us/step - loss: 12.1972
1/1 [==============================] - 0s 133ms/step - loss: 12.1972 - val_loss: 10.5415
Epoch 16/100
1/1 [==============================] - 0s 12us/step - loss: 10.0288
1/1 [==============================] - 0s 134ms/step - loss: 10.0288 - val_loss: 8.7276
Epoch 17/100
1/1 [==============================] - 0s 14us/step - loss: 8.2727
1/1 [==============================] - 0s 136ms/step - loss: 8.2727 - val_loss: 7.2532
Epoch 18/100
1/1 [==============================] - 0s 14us/step - loss: 6.8504
1/1 [==============================] - 0s 135ms/step - loss: 6.8504 - val_loss: 6.0545
Epoch 19/100
1/1 [==============================] - 0s 13us/step - loss: 5.6986
1/1 [==============================] - 0s 134ms/step - loss: 5.6986 - val_loss: 5.0795
Epoch 20/100
1/1 [==============================] - 0s 14us/step - loss: 4.7657
1/1 [==============================] - 0s 144ms/step - loss: 4.7657 - val_loss: 4.2860
Epoch 21/100
1/1 [==============================] - 0s 12us/step - loss: 4.0101
1/1 [==============================] - 0s 135ms/step - loss: 4.0101 - val_loss: 3.6400
Epoch 22/100
1/1 [==============================] - 0s 15us/step - loss: 3.3982
1/1 [==============================] - 0s 137ms/step - loss: 3.3982 - val_loss: 3.1136
Epoch 23/100
1/1 [==============================] - 0s 12us/step - loss: 2.9026
1/1 [==============================] - 0s 134ms/step - loss: 2.9026 - val_loss: 2.6846
Epoch 24/100
1/1 [==============================] - 0s 13us/step - loss: 2.5012
1/1 [==============================] - 0s 134ms/step - loss: 2.5012 - val_loss: 2.3346
Epoch 25/100
1/1 [==============================] - 0s 14us/step - loss: 2.1761
1/1 [==============================] - 0s 133ms/step - loss: 2.1761 - val_loss: 2.0489
Epoch 26/100
1/1 [==============================] - 0s 13us/step - loss: 1.9128
1/1 [==============================] - 0s 136ms/step - loss: 1.9128 - val_loss: 1.8155
Epoch 27/100
1/1 [==============================] - 0s 11us/step - loss: 1.6996
1/1 [==============================] - 0s 134ms/step - loss: 1.6996 - val_loss: 1.6247
Epoch 28/100
1/1 [==============================] - 0s 11us/step - loss: 1.5269
1/1 [==============================] - 0s 136ms/step - loss: 1.5269 - val_loss: 1.4685
Epoch 29/100
1/1 [==============================] - 0s 14us/step - loss: 1.3870
1/1 [==============================] - 0s 134ms/step - loss: 1.3870 - val_loss: 1.3405
Epoch 30/100
1/1 [==============================] - 0s 14us/step - loss: 1.2737
1/1 [==============================] - 0s 143ms/step - loss: 1.2737 - val_loss: 1.2355
Epoch 31/100
1/1 [==============================] - 0s 14us/step - loss: 1.1820
1/1 [==============================] - 0s 133ms/step - loss: 1.1820 - val_loss: 1.1493
Epoch 32/100
1/1 [==============================] - 0s 15us/step - loss: 1.1076
1/1 [==============================] - 0s 134ms/step - loss: 1.1076 - val_loss: 1.0784
Epoch 33/100
1/1 [==============================] - 0s 13us/step - loss: 1.0474
1/1 [==============================] - 0s 134ms/step - loss: 1.0474 - val_loss: 1.0200
Epoch 34/100
1/1 [==============================] - 0s 18us/step - loss: 0.9987
1/1 [==============================] - 0s 135ms/step - loss: 0.9987 - val_loss: 0.9719
Epoch 35/100
1/1 [==============================] - 0s 12us/step - loss: 0.9592
1/1 [==============================] - 0s 140ms/step - loss: 0.9592 - val_loss: 0.9321
Epoch 36/100
1/1 [==============================] - 0s 14us/step - loss: 0.9272
1/1 [==============================] - 0s 137ms/step - loss: 0.9272 - val_loss: 0.8992
Epoch 37/100
1/1 [==============================] - 0s 14us/step - loss: 0.9013
1/1 [==============================] - 0s 134ms/step - loss: 0.9013 - val_loss: 0.8719
Epoch 38/100
1/1 [==============================] - 0s 15us/step - loss: 0.8804
1/1 [==============================] - 0s 136ms/step - loss: 0.8804 - val_loss: 0.8492
Epoch 39/100
1/1 [==============================] - 0s 14us/step - loss: 0.8634
1/1 [==============================] - 0s 142ms/step - loss: 0.8634 - val_loss: 0.8303
Epoch 40/100
1/1 [==============================] - 0s 13us/step - loss: 0.8496
1/1 [==============================] - 0s 134ms/step - loss: 0.8496 - val_loss: 0.8145
Epoch 41/100
1/1 [==============================] - 0s 13us/step - loss: 0.8385
1/1 [==============================] - 0s 134ms/step - loss: 0.8385 - val_loss: 0.8014
Epoch 42/100
1/1 [==============================] - 0s 25us/step - loss: 0.8294
1/1 [==============================] - 0s 138ms/step - loss: 0.8294 - val_loss: 0.7903
Epoch 43/100
1/1 [==============================] - 0s 12us/step - loss: 0.8221
1/1 [==============================] - 0s 134ms/step - loss: 0.8221 - val_loss: 0.7811
Epoch 44/100
1/1 [==============================] - 0s 11us/step - loss: 0.8162
1/1 [==============================] - 0s 133ms/step - loss: 0.8162 - val_loss: 0.7732
Epoch 45/100
1/1 [==============================] - 0s 14us/step - loss: 0.8114
1/1 [==============================] - 0s 137ms/step - loss: 0.8114 - val_loss: 0.7666
Epoch 46/100
1/1 [==============================] - 0s 13us/step - loss: 0.8075
1/1 [==============================] - 0s 135ms/step - loss: 0.8075 - val_loss: 0.7610
Epoch 47/100
1/1 [==============================] - 0s 13us/step - loss: 0.8044
1/1 [==============================] - 0s 134ms/step - loss: 0.8044 - val_loss: 0.7563
Epoch 48/100
1/1 [==============================] - 0s 13us/step - loss: 0.8018
1/1 [==============================] - 0s 134ms/step - loss: 0.8018 - val_loss: 0.7522
Epoch 49/100
1/1 [==============================] - 0s 10us/step - loss: 0.7998
1/1 [==============================] - 0s 142ms/step - loss: 0.7998 - val_loss: 0.7488
Epoch 50/100
1/1 [==============================] - 0s 15us/step - loss: 0.7981
1/1 [==============================] - 0s 134ms/step - loss: 0.7981 - val_loss: 0.7458
Epoch 51/100
1/1 [==============================] - 0s 12us/step - loss: 0.7967
1/1 [==============================] - 0s 133ms/step - loss: 0.7967 - val_loss: 0.7433
Epoch 52/100
1/1 [==============================] - 0s 14us/step - loss: 0.7956
1/1 [==============================] - 0s 136ms/step - loss: 0.7956 - val_loss: 0.7411
Epoch 53/100
1/1 [==============================] - 0s 13us/step - loss: 0.7948
1/1 [==============================] - 0s 136ms/step - loss: 0.7948 - val_loss: 0.7392
Epoch 54/100
1/1 [==============================] - 0s 13us/step - loss: 0.7940
1/1 [==============================] - 0s 139ms/step - loss: 0.7940 - val_loss: 0.7376
Epoch 55/100
1/1 [==============================] - 0s 13us/step - loss: 0.7934
1/1 [==============================] - 0s 133ms/step - loss: 0.7934 - val_loss: 0.7361
Epoch 56/100
1/1 [==============================] - 0s 11us/step - loss: 0.7930
1/1 [==============================] - 0s 151ms/step - loss: 0.7930 - val_loss: 0.7349
Epoch 57/100
1/1 [==============================] - 0s 14us/step - loss: 0.7926
1/1 [==============================] - 0s 138ms/step - loss: 0.7926 - val_loss: 0.7338
Epoch 58/100
1/1 [==============================] - 0s 14us/step - loss: 0.7923
1/1 [==============================] - 0s 135ms/step - loss: 0.7923 - val_loss: 0.7329
Epoch 59/100
1/1 [==============================] - 0s 13us/step - loss: 0.7920
1/1 [==============================] - 0s 143ms/step - loss: 0.7920 - val_loss: 0.7321
Epoch 60/100
1/1 [==============================] - 0s 12us/step - loss: 0.7918
1/1 [==============================] - 0s 134ms/step - loss: 0.7918 - val_loss: 0.7313
Epoch 61/100
1/1 [==============================] - 0s 11us/step - loss: 0.7917
1/1 [==============================] - 0s 136ms/step - loss: 0.7917 - val_loss: 0.7307
Epoch 62/100
1/1 [==============================] - 0s 13us/step - loss: 0.7915
1/1 [==============================] - 0s 134ms/step - loss: 0.7915 - val_loss: 0.7301
Epoch 63/100
1/1 [==============================] - 0s 11us/step - loss: 0.7914
1/1 [==============================] - 0s 134ms/step - loss: 0.7914 - val_loss: 0.7297
Epoch 64/100
1/1 [==============================] - 0s 12us/step - loss: 0.7913
1/1 [==============================] - 0s 135ms/step - loss: 0.7913 - val_loss: 0.7292
Epoch 65/100
1/1 [==============================] - 0s 13us/step - loss: 0.7913
1/1 [==============================] - 0s 138ms/step - loss: 0.7913 - val_loss: 0.7288
Epoch 66/100
1/1 [==============================] - 0s 14us/step - loss: 0.7912
1/1 [==============================] - 0s 137ms/step - loss: 0.7912 - val_loss: 0.7285
Epoch 67/100
1/1 [==============================] - 0s 13us/step - loss: 0.7912
1/1 [==============================] - 0s 138ms/step - loss: 0.7912 - val_loss: 0.7282
Epoch 68/100
1/1 [==============================] - 0s 14us/step - loss: 0.7911
1/1 [==============================] - 0s 143ms/step - loss: 0.7911 - val_loss: 0.7279
Epoch 69/100
1/1 [==============================] - 0s 12us/step - loss: 0.7911
1/1 [==============================] - 0s 133ms/step - loss: 0.7911 - val_loss: 0.7277
Epoch 70/100
1/1 [==============================] - 0s 11us/step - loss: 0.7911
1/1 [==============================] - 0s 134ms/step - loss: 0.7911 - val_loss: 0.7274
Epoch 71/100
1/1 [==============================] - 0s 14us/step - loss: 0.7911
1/1 [==============================] - 0s 134ms/step - loss: 0.7911 - val_loss: 0.7273
Epoch 72/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7271
Epoch 73/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7269
Epoch 74/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7268
Epoch 75/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 138ms/step - loss: 0.7910 - val_loss: 0.7267
Epoch 76/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7266
Epoch 77/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7265
Epoch 78/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 144ms/step - loss: 0.7910 - val_loss: 0.7264
Epoch 79/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7263
Epoch 80/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7262
Epoch 81/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7262
Epoch 82/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7261
Epoch 83/100
1/1 [==============================] - 0s 17us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7261
Epoch 84/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7260
Epoch 85/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 138ms/step - loss: 0.7910 - val_loss: 0.7260
Epoch 86/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 87/100
1/1 [==============================] - 0s 12us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 88/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 143ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 89/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 90/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 91/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 92/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 93/100
1/1 [==============================] - 0s 15us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 94/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 132ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 95/100
1/1 [==============================] - 0s 29us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 96/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 97/100
1/1 [==============================] - 0s 13us/step - loss: 0.7910
1/1 [==============================] - 0s 142ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 98/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 132ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 99/100
1/1 [==============================] - 0s 37us/step - loss: 0.7910
1/1 [==============================] - 0s 138ms/step - loss: 0.7910 - val_loss: 0.7257
Epoch 100/100
1/1 [==============================] - 0s 17us/step - loss: 0.7910
1/1 [==============================] - 0s 137ms/step - loss: 0.7910 - val_loss: 0.7257
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-39-26Z
Training run 7/8 (flags = list(64, 0.001, 1000, 30, "sigmoid"))
Using run directory runs/2020-11-02T19-39-41Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/30
1/1 [==============================] - 0s 11us/step - loss: 45.0582
1/1 [==============================] - 1s 578ms/step - loss: 45.0582 - val_loss: 42.6221
Epoch 2/30
1/1 [==============================] - 0s 16us/step - loss: 41.4483
1/1 [==============================] - 0s 136ms/step - loss: 41.4483 - val_loss: 39.2637
Epoch 3/30
1/1 [==============================] - 0s 17us/step - loss: 38.1376
1/1 [==============================] - 0s 140ms/step - loss: 38.1376 - val_loss: 36.1791
Epoch 4/30
1/1 [==============================] - 0s 15us/step - loss: 35.0990
1/1 [==============================] - 0s 137ms/step - loss: 35.0990 - val_loss: 33.3439
Epoch 5/30
1/1 [==============================] - 0s 15us/step - loss: 32.3081
1/1 [==============================] - 0s 136ms/step - loss: 32.3081 - val_loss: 30.7363
Epoch 6/30
1/1 [==============================] - 0s 15us/step - loss: 29.7433
1/1 [==============================] - 0s 136ms/step - loss: 29.7433 - val_loss: 28.3371
Epoch 7/30
1/1 [==============================] - 0s 9us/step - loss: 27.3853
1/1 [==============================] - 0s 131ms/step - loss: 27.3853 - val_loss: 26.1286
Epoch 8/30
1/1 [==============================] - 0s 11us/step - loss: 25.2166
1/1 [==============================] - 0s 130ms/step - loss: 25.2166 - val_loss: 24.0952
Epoch 9/30
1/1 [==============================] - 0s 10us/step - loss: 23.2216
1/1 [==============================] - 0s 139ms/step - loss: 23.2216 - val_loss: 22.2227
Epoch 10/30
1/1 [==============================] - 0s 13us/step - loss: 21.3861
1/1 [==============================] - 0s 135ms/step - loss: 21.3861 - val_loss: 20.4980
Epoch 11/30
1/1 [==============================] - 0s 11us/step - loss: 19.6971
1/1 [==============================] - 0s 136ms/step - loss: 19.6971 - val_loss: 18.9095
Epoch 12/30
1/1 [==============================] - 0s 13us/step - loss: 18.1431
1/1 [==============================] - 0s 133ms/step - loss: 18.1431 - val_loss: 17.4464
Epoch 13/30
1/1 [==============================] - 0s 11us/step - loss: 16.7132
1/1 [==============================] - 0s 136ms/step - loss: 16.7132 - val_loss: 16.0988
Epoch 14/30
1/1 [==============================] - 0s 12us/step - loss: 15.3977
1/1 [==============================] - 0s 134ms/step - loss: 15.3977 - val_loss: 14.8578
Epoch 15/30
1/1 [==============================] - 0s 17us/step - loss: 14.1876
1/1 [==============================] - 0s 136ms/step - loss: 14.1876 - val_loss: 13.7150
Epoch 16/30
1/1 [==============================] - 0s 19us/step - loss: 13.0746
1/1 [==============================] - 0s 137ms/step - loss: 13.0746 - val_loss: 12.6629
Epoch 17/30
1/1 [==============================] - 0s 15us/step - loss: 12.0511
1/1 [==============================] - 0s 136ms/step - loss: 12.0511 - val_loss: 11.6943
Epoch 18/30
1/1 [==============================] - 0s 16us/step - loss: 11.1102
1/1 [==============================] - 0s 135ms/step - loss: 11.1102 - val_loss: 10.8030
Epoch 19/30
1/1 [==============================] - 0s 15us/step - loss: 10.2455
1/1 [==============================] - 0s 141ms/step - loss: 10.2455 - val_loss: 9.9828
Epoch 20/30
1/1 [==============================] - 0s 15us/step - loss: 9.4510
1/1 [==============================] - 0s 135ms/step - loss: 9.4510 - val_loss: 9.2283
Epoch 21/30
1/1 [==============================] - 0s 9us/step - loss: 8.7212
1/1 [==============================] - 0s 134ms/step - loss: 8.7212 - val_loss: 8.5344
Epoch 22/30
1/1 [==============================] - 0s 18us/step - loss: 8.0510
1/1 [==============================] - 0s 134ms/step - loss: 8.0510 - val_loss: 7.8963
Epoch 23/30
1/1 [==============================] - 0s 13us/step - loss: 7.4359
1/1 [==============================] - 0s 132ms/step - loss: 7.4359 - val_loss: 7.3098
Epoch 24/30
1/1 [==============================] - 0s 9us/step - loss: 6.8713
1/1 [==============================] - 0s 132ms/step - loss: 6.8713 - val_loss: 6.7708
Epoch 25/30
1/1 [==============================] - 0s 10us/step - loss: 6.3534
1/1 [==============================] - 0s 132ms/step - loss: 6.3534 - val_loss: 6.2756
Epoch 26/30
1/1 [==============================] - 0s 11us/step - loss: 5.8785
1/1 [==============================] - 0s 134ms/step - loss: 5.8785 - val_loss: 5.8207
Epoch 27/30
1/1 [==============================] - 0s 17us/step - loss: 5.4431
1/1 [==============================] - 0s 136ms/step - loss: 5.4431 - val_loss: 5.4029
Epoch 28/30
1/1 [==============================] - 0s 16us/step - loss: 5.0441
1/1 [==============================] - 0s 141ms/step - loss: 5.0441 - val_loss: 5.0194
Epoch 29/30
1/1 [==============================] - 0s 11us/step - loss: 4.6786
1/1 [==============================] - 0s 135ms/step - loss: 4.6786 - val_loss: 4.6673
Epoch 30/30
1/1 [==============================] - 0s 20us/step - loss: 4.3438
1/1 [==============================] - 0s 137ms/step - loss: 4.3438 - val_loss: 4.3442
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-39-41Z
Training run 8/8 (flags = list(64, 0.001, 200, 30, "tanh"))
Using run directory runs/2020-11-02T19-39-46Z
> FLAGS <- flags(
+ flag_numeric("nodes", 50),
+ flag_numeric("batch_size", 100),
+ flag_string("activation", "relu"),
+ .... [TRUNCATED]
> model <- keras_model_sequential()
> model %>%
+ layer_dense( units = FLAGS$nodes, activation = FLAGS$activation, input_shape = dim(hitters_scale_train)[2]) %>%
+ layer_ .... [TRUNCATED]
> set.seed(1)
> model %>% compile (
+ loss = 'mse',
+ optimizer = optimizer_sgd(lr=FLAGS$learning_rate))
> model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = .... [TRUNCATED]
Epoch 1/30
1/2 [==============>...............] - ETA: 0s - loss: 37.7147
2/2 [==============================] - 0s 727us/step - loss: 37.9011
2/2 [==============================] - 1s 291ms/step - loss: 37.9011 - val_loss: 36.3405
Epoch 2/30
1/2 [==============>...............] - ETA: 0s - loss: 35.7724
2/2 [==============================] - 0s 1ms/step - loss: 35.8196
2/2 [==============================] - 0s 71ms/step - loss: 35.8196 - val_loss: 34.7922
Epoch 3/30
1/2 [==============>...............] - ETA: 0s - loss: 33.8228
2/2 [==============================] - 0s 798us/step - loss: 33.8059
2/2 [==============================] - 0s 70ms/step - loss: 33.8059 - val_loss: 33.2080
Epoch 4/30
1/2 [==============>...............] - ETA: 0s - loss: 32.2774
2/2 [==============================] - 0s 1ms/step - loss: 32.1180
2/2 [==============================] - 0s 71ms/step - loss: 32.1180 - val_loss: 31.7447
Epoch 5/30
1/2 [==============>...............] - ETA: 0s - loss: 30.6944
2/2 [==============================] - 0s 928us/step - loss: 30.3946
2/2 [==============================] - 0s 72ms/step - loss: 30.3946 - val_loss: 30.2341
Epoch 6/30
1/2 [==============>...............] - ETA: 0s - loss: 28.8608
2/2 [==============================] - 0s 1ms/step - loss: 28.7849
2/2 [==============================] - 0s 68ms/step - loss: 28.7849 - val_loss: 28.8368
Epoch 7/30
1/2 [==============>...............] - ETA: 0s - loss: 27.1999
2/2 [==============================] - 0s 764us/step - loss: 27.1317
2/2 [==============================] - 0s 68ms/step - loss: 27.1317 - val_loss: 27.5972
Epoch 8/30
1/2 [==============>...............] - ETA: 0s - loss: 25.3265
2/2 [==============================] - 0s 874us/step - loss: 25.4889
2/2 [==============================] - 0s 68ms/step - loss: 25.4889 - val_loss: 26.0265
Epoch 9/30
1/2 [==============>...............] - ETA: 0s - loss: 23.8127
2/2 [==============================] - 0s 822us/step - loss: 23.8960
2/2 [==============================] - 0s 68ms/step - loss: 23.8960 - val_loss: 24.4745
Epoch 10/30
1/2 [==============>...............] - ETA: 0s - loss: 22.5028
2/2 [==============================] - 0s 816us/step - loss: 22.3516
2/2 [==============================] - 0s 70ms/step - loss: 22.3516 - val_loss: 23.0624
Epoch 11/30
1/2 [==============>...............] - ETA: 0s - loss: 21.0304
2/2 [==============================] - 0s 906us/step - loss: 20.8613
2/2 [==============================] - 0s 68ms/step - loss: 20.8613 - val_loss: 21.7092
Epoch 12/30
1/2 [==============>...............] - ETA: 0s - loss: 19.5360
2/2 [==============================] - 0s 721us/step - loss: 19.4177
2/2 [==============================] - 0s 68ms/step - loss: 19.4177 - val_loss: 20.3435
Epoch 13/30
1/2 [==============>...............] - ETA: 0s - loss: 18.2716
2/2 [==============================] - 0s 955us/step - loss: 17.9488
2/2 [==============================] - 0s 68ms/step - loss: 17.9488 - val_loss: 19.2287
Epoch 14/30
1/2 [==============>...............] - ETA: 0s - loss: 16.6198
2/2 [==============================] - 0s 1ms/step - loss: 16.6304
2/2 [==============================] - 0s 68ms/step - loss: 16.6304 - val_loss: 17.8024
Epoch 15/30
1/2 [==============>...............] - ETA: 0s - loss: 15.3170
2/2 [==============================] - 0s 900us/step - loss: 15.2614
2/2 [==============================] - 0s 67ms/step - loss: 15.2614 - val_loss: 16.3983
Epoch 16/30
1/2 [==============>...............] - ETA: 0s - loss: 14.0793
2/2 [==============================] - 0s 591us/step - loss: 13.9897
2/2 [==============================] - 0s 67ms/step - loss: 13.9897 - val_loss: 15.2999
Epoch 17/30
1/2 [==============>...............] - ETA: 0s - loss: 12.9916
2/2 [==============================] - 0s 623us/step - loss: 12.7835
2/2 [==============================] - 0s 67ms/step - loss: 12.7835 - val_loss: 14.2970
Epoch 18/30
1/2 [==============>...............] - ETA: 0s - loss: 11.5383
2/2 [==============================] - 0s 785us/step - loss: 11.5838
2/2 [==============================] - 0s 69ms/step - loss: 11.5838 - val_loss: 12.9356
Epoch 19/30
1/2 [==============>...............] - ETA: 0s - loss: 10.4690
2/2 [==============================] - 0s 857us/step - loss: 10.3876
2/2 [==============================] - 0s 69ms/step - loss: 10.3876 - val_loss: 11.9494
Epoch 20/30
1/2 [==============>...............] - ETA: 0s - loss: 9.4706
2/2 [==============================] - 0s 988us/step - loss: 9.3483
2/2 [==============================] - 0s 70ms/step - loss: 9.3483 - val_loss: 10.6828
Epoch 21/30
1/2 [==============>...............] - ETA: 0s - loss: 8.5980
2/2 [==============================] - 0s 877us/step - loss: 8.3562
2/2 [==============================] - 0s 68ms/step - loss: 8.3562 - val_loss: 9.8885
Epoch 22/30
1/2 [==============>...............] - ETA: 0s - loss: 7.8175
2/2 [==============================] - 0s 800us/step - loss: 7.5959
2/2 [==============================] - 0s 68ms/step - loss: 7.5959 - val_loss: 9.0446
Epoch 23/30
1/2 [==============>...............] - ETA: 0s - loss: 6.9850
2/2 [==============================] - 0s 922us/step - loss: 6.8576
2/2 [==============================] - 0s 69ms/step - loss: 6.8576 - val_loss: 8.2814
Epoch 24/30
1/2 [==============>...............] - ETA: 0s - loss: 6.2094
2/2 [==============================] - 0s 834us/step - loss: 6.1709
2/2 [==============================] - 0s 68ms/step - loss: 6.1709 - val_loss: 7.5660
Epoch 25/30
1/2 [==============>...............] - ETA: 0s - loss: 5.4239
2/2 [==============================] - 0s 831us/step - loss: 5.4941
2/2 [==============================] - 0s 69ms/step - loss: 5.4941 - val_loss: 6.8004
Epoch 26/30
1/2 [==============>...............] - ETA: 0s - loss: 5.0382
2/2 [==============================] - 0s 1ms/step - loss: 4.9161
2/2 [==============================] - 0s 69ms/step - loss: 4.9161 - val_loss: 6.1897
Epoch 27/30
1/2 [==============>...............] - ETA: 0s - loss: 4.4073
2/2 [==============================] - 0s 989us/step - loss: 4.3986
2/2 [==============================] - 0s 68ms/step - loss: 4.3986 - val_loss: 5.4900
Epoch 28/30
1/2 [==============>...............] - ETA: 0s - loss: 3.8023
2/2 [==============================] - 0s 754us/step - loss: 3.8884
2/2 [==============================] - 0s 67ms/step - loss: 3.8884 - val_loss: 4.9387
Epoch 29/30
1/2 [==============>...............] - ETA: 0s - loss: 3.5314
2/2 [==============================] - 0s 788us/step - loss: 3.4492
2/2 [==============================] - 0s 71ms/step - loss: 3.4492 - val_loss: 4.5482
Epoch 30/30
1/2 [==============>...............] - ETA: 0s - loss: 3.0471
2/2 [==============================] - 0s 904us/step - loss: 3.1376
2/2 [==============================] - 0s 68ms/step - loss: 3.1376 - val_loss: 4.0796
Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-11-02T19-39-46Z
runs
Data frame: 8 x 23
# ... with 20 more columns:
# flag_nodes, flag_batch_size, flag_activation, flag_learning_rate, flag_epochs,
# epochs, epochs_completed, metrics, model, loss_function, optimizer,
# learning_rate, script, start, end, completed, output, source_code, context, type
• Print the returned value from tf_runs to see the metrics for each run. Which run ( which hyper-parameter combination) gave the best mean squared error on the validation data?
The combination from the third run
• Print the learning curve for your best model. Does your best model still overfit?
Yes, the validation loss is less than the metric loss
• Does your validation_loss stop decreasing after several epochs? If so, at roughly which epoch does your validation_loss stop decreasing?
Yes, it stops decreasing at the 94th epoch.
model <- keras_model_sequential()
model %>%
layer_dense( units = 392, activation = "sigmoid", input_shape = dim(hitters_scale_train)[2]) %>%
layer_dense( units = 392, activation = "sigmoid") %>%
layer_dense( units = 392, activation = "sigmoid") %>%
layer_dense( units = 1)
set.seed(1)
model %>% compile (
loss = 'mse',
optimizer = optimizer_sgd(0.05))
model %>% fit (x = as.matrix(hitters_scale_train), y = hitters_train_labels, epochs = 100, batch_size = 500, validation_data = list(as.matrix(hitters_scale_val), hitters_val_labels))
Epoch 1/100
1/1 [==============================] - 0s 20us/step - loss: 47.2539
1/1 [==============================] - 1s 585ms/step - loss: 47.2539 - val_loss: 4503.0488
Epoch 2/100
1/1 [==============================] - 0s 14us/step - loss: 4516.8154
1/1 [==============================] - 0s 136ms/step - loss: 4516.8154 - val_loss: 147.4994
Epoch 3/100
1/1 [==============================] - 0s 15us/step - loss: 145.2776
1/1 [==============================] - 0s 137ms/step - loss: 145.2776 - val_loss: 119.2426
Epoch 4/100
1/1 [==============================] - 0s 17us/step - loss: 117.2549
1/1 [==============================] - 0s 136ms/step - loss: 117.2549 - val_loss: 96.8352
Epoch 5/100
1/1 [==============================] - 0s 12us/step - loss: 95.0535
1/1 [==============================] - 0s 136ms/step - loss: 95.0535 - val_loss: 78.7034
Epoch 6/100
1/1 [==============================] - 0s 16us/step - loss: 77.1069
1/1 [==============================] - 0s 137ms/step - loss: 77.1069 - val_loss: 64.0155
Epoch 7/100
1/1 [==============================] - 0s 11us/step - loss: 62.5854
1/1 [==============================] - 0s 143ms/step - loss: 62.5854 - val_loss: 52.1112
Epoch 8/100
1/1 [==============================] - 0s 17us/step - loss: 50.8308
1/1 [==============================] - 0s 135ms/step - loss: 50.8308 - val_loss: 42.4598
Epoch 9/100
1/1 [==============================] - 0s 14us/step - loss: 41.3141
1/1 [==============================] - 0s 133ms/step - loss: 41.3141 - val_loss: 34.6328
Epoch 10/100
1/1 [==============================] - 0s 16us/step - loss: 33.6084
1/1 [==============================] - 0s 135ms/step - loss: 33.6084 - val_loss: 28.2839
Epoch 11/100
1/1 [==============================] - 0s 15us/step - loss: 27.3686
1/1 [==============================] - 0s 147ms/step - loss: 27.3686 - val_loss: 23.1328
Epoch 12/100
1/1 [==============================] - 0s 12us/step - loss: 22.3156
1/1 [==============================] - 0s 133ms/step - loss: 22.3156 - val_loss: 18.9524
Epoch 13/100
1/1 [==============================] - 0s 14us/step - loss: 18.2235
1/1 [==============================] - 0s 134ms/step - loss: 18.2235 - val_loss: 15.5589
Epoch 14/100
1/1 [==============================] - 0s 12us/step - loss: 14.9095
1/1 [==============================] - 0s 133ms/step - loss: 14.9095 - val_loss: 12.8035
Epoch 15/100
1/1 [==============================] - 0s 17us/step - loss: 12.2256
1/1 [==============================] - 0s 139ms/step - loss: 12.2256 - val_loss: 10.5655
Epoch 16/100
1/1 [==============================] - 0s 16us/step - loss: 10.0520
1/1 [==============================] - 0s 136ms/step - loss: 10.0520 - val_loss: 8.7472
Epoch 17/100
1/1 [==============================] - 0s 18us/step - loss: 8.2916
1/1 [==============================] - 0s 145ms/step - loss: 8.2916 - val_loss: 7.2693
Epoch 18/100
1/1 [==============================] - 0s 16us/step - loss: 6.8658
1/1 [==============================] - 0s 136ms/step - loss: 6.8658 - val_loss: 6.0677
Epoch 19/100
1/1 [==============================] - 0s 11us/step - loss: 5.7111
1/1 [==============================] - 0s 136ms/step - loss: 5.7111 - val_loss: 5.0903
Epoch 20/100
1/1 [==============================] - 0s 19us/step - loss: 4.7759
1/1 [==============================] - 0s 138ms/step - loss: 4.7759 - val_loss: 4.2949
Epoch 21/100
1/1 [==============================] - 0s 11us/step - loss: 4.0185
1/1 [==============================] - 0s 138ms/step - loss: 4.0185 - val_loss: 3.6472
Epoch 22/100
1/1 [==============================] - 0s 12us/step - loss: 3.4050
1/1 [==============================] - 0s 136ms/step - loss: 3.4050 - val_loss: 3.1196
Epoch 23/100
1/1 [==============================] - 0s 12us/step - loss: 2.9082
1/1 [==============================] - 0s 135ms/step - loss: 2.9082 - val_loss: 2.6895
Epoch 24/100
1/1 [==============================] - 0s 18us/step - loss: 2.5058
1/1 [==============================] - 0s 136ms/step - loss: 2.5058 - val_loss: 2.3387
Epoch 25/100
1/1 [==============================] - 0s 12us/step - loss: 2.1799
1/1 [==============================] - 0s 134ms/step - loss: 2.1799 - val_loss: 2.0523
Epoch 26/100
1/1 [==============================] - 0s 13us/step - loss: 1.9159
1/1 [==============================] - 0s 138ms/step - loss: 1.9159 - val_loss: 1.8183
Epoch 27/100
1/1 [==============================] - 0s 14us/step - loss: 1.7021
1/1 [==============================] - 0s 143ms/step - loss: 1.7021 - val_loss: 1.6270
Epoch 28/100
1/1 [==============================] - 0s 11us/step - loss: 1.5289
1/1 [==============================] - 0s 138ms/step - loss: 1.5289 - val_loss: 1.4704
Epoch 29/100
1/1 [==============================] - 0s 11us/step - loss: 1.3887
1/1 [==============================] - 0s 133ms/step - loss: 1.3887 - val_loss: 1.3421
Epoch 30/100
1/1 [==============================] - 0s 12us/step - loss: 1.2751
1/1 [==============================] - 0s 134ms/step - loss: 1.2751 - val_loss: 1.2369
Epoch 31/100
1/1 [==============================] - 0s 11us/step - loss: 1.1831
1/1 [==============================] - 0s 134ms/step - loss: 1.1831 - val_loss: 1.1504
Epoch 32/100
1/1 [==============================] - 0s 13us/step - loss: 1.1086
1/1 [==============================] - 0s 136ms/step - loss: 1.1086 - val_loss: 1.0793
Epoch 33/100
1/1 [==============================] - 0s 11us/step - loss: 1.0482
1/1 [==============================] - 0s 139ms/step - loss: 1.0482 - val_loss: 1.0208
Epoch 34/100
1/1 [==============================] - 0s 17us/step - loss: 0.9993
1/1 [==============================] - 0s 133ms/step - loss: 0.9993 - val_loss: 0.9725
Epoch 35/100
1/1 [==============================] - 0s 13us/step - loss: 0.9598
1/1 [==============================] - 0s 133ms/step - loss: 0.9598 - val_loss: 0.9327
Epoch 36/100
1/1 [==============================] - 0s 14us/step - loss: 0.9277
1/1 [==============================] - 0s 140ms/step - loss: 0.9277 - val_loss: 0.8997
Epoch 37/100
1/1 [==============================] - 0s 16us/step - loss: 0.9017
1/1 [==============================] - 0s 133ms/step - loss: 0.9017 - val_loss: 0.8723
Epoch 38/100
1/1 [==============================] - 0s 12us/step - loss: 0.8807
1/1 [==============================] - 0s 135ms/step - loss: 0.8807 - val_loss: 0.8496
Epoch 39/100
1/1 [==============================] - 0s 11us/step - loss: 0.8636
1/1 [==============================] - 0s 135ms/step - loss: 0.8636 - val_loss: 0.8306
Epoch 40/100
1/1 [==============================] - 0s 21us/step - loss: 0.8498
1/1 [==============================] - 0s 140ms/step - loss: 0.8498 - val_loss: 0.8148
Epoch 41/100
1/1 [==============================] - 0s 14us/step - loss: 0.8387
1/1 [==============================] - 0s 135ms/step - loss: 0.8387 - val_loss: 0.8016
Epoch 42/100
1/1 [==============================] - 0s 11us/step - loss: 0.8296
1/1 [==============================] - 0s 133ms/step - loss: 0.8296 - val_loss: 0.7906
Epoch 43/100
1/1 [==============================] - 0s 13us/step - loss: 0.8223
1/1 [==============================] - 0s 136ms/step - loss: 0.8223 - val_loss: 0.7813
Epoch 44/100
1/1 [==============================] - 0s 14us/step - loss: 0.8163
1/1 [==============================] - 0s 137ms/step - loss: 0.8163 - val_loss: 0.7734
Epoch 45/100
1/1 [==============================] - 0s 15us/step - loss: 0.8115
1/1 [==============================] - 0s 136ms/step - loss: 0.8115 - val_loss: 0.7668
Epoch 46/100
1/1 [==============================] - 0s 17us/step - loss: 0.8076
1/1 [==============================] - 0s 143ms/step - loss: 0.8076 - val_loss: 0.7612
Epoch 47/100
1/1 [==============================] - 0s 17us/step - loss: 0.8045
1/1 [==============================] - 0s 139ms/step - loss: 0.8045 - val_loss: 0.7564
Epoch 48/100
1/1 [==============================] - 0s 15us/step - loss: 0.8019
1/1 [==============================] - 0s 135ms/step - loss: 0.8019 - val_loss: 0.7524
Epoch 49/100
1/1 [==============================] - 0s 16us/step - loss: 0.7999
1/1 [==============================] - 0s 136ms/step - loss: 0.7999 - val_loss: 0.7489
Epoch 50/100
1/1 [==============================] - 0s 15us/step - loss: 0.7982
1/1 [==============================] - 0s 135ms/step - loss: 0.7982 - val_loss: 0.7460
Epoch 51/100
1/1 [==============================] - 0s 15us/step - loss: 0.7968
1/1 [==============================] - 0s 134ms/step - loss: 0.7968 - val_loss: 0.7434
Epoch 52/100
1/1 [==============================] - 0s 20us/step - loss: 0.7957
1/1 [==============================] - 0s 136ms/step - loss: 0.7957 - val_loss: 0.7412
Epoch 53/100
1/1 [==============================] - 0s 17us/step - loss: 0.7948
1/1 [==============================] - 0s 134ms/step - loss: 0.7948 - val_loss: 0.7393
Epoch 54/100
1/1 [==============================] - 0s 14us/step - loss: 0.7941
1/1 [==============================] - 0s 135ms/step - loss: 0.7941 - val_loss: 0.7377
Epoch 55/100
1/1 [==============================] - 0s 18us/step - loss: 0.7935
1/1 [==============================] - 0s 136ms/step - loss: 0.7935 - val_loss: 0.7363
Epoch 56/100
1/1 [==============================] - 0s 12us/step - loss: 0.7931
1/1 [==============================] - 1s 511ms/step - loss: 0.7931 - val_loss: 0.7350
Epoch 57/100
1/1 [==============================] - 0s 14us/step - loss: 0.7927
1/1 [==============================] - 0s 137ms/step - loss: 0.7927 - val_loss: 0.7339
Epoch 58/100
1/1 [==============================] - 0s 15us/step - loss: 0.7924
1/1 [==============================] - 0s 138ms/step - loss: 0.7924 - val_loss: 0.7330
Epoch 59/100
1/1 [==============================] - 0s 16us/step - loss: 0.7921
1/1 [==============================] - 0s 138ms/step - loss: 0.7921 - val_loss: 0.7322
Epoch 60/100
1/1 [==============================] - 0s 12us/step - loss: 0.7919
1/1 [==============================] - 0s 132ms/step - loss: 0.7919 - val_loss: 0.7314
Epoch 61/100
1/1 [==============================] - 0s 16us/step - loss: 0.7917
1/1 [==============================] - 0s 134ms/step - loss: 0.7917 - val_loss: 0.7308
Epoch 62/100
1/1 [==============================] - 0s 16us/step - loss: 0.7916
1/1 [==============================] - 0s 134ms/step - loss: 0.7916 - val_loss: 0.7302
Epoch 63/100
1/1 [==============================] - 0s 18us/step - loss: 0.7915
1/1 [==============================] - 0s 136ms/step - loss: 0.7915 - val_loss: 0.7297
Epoch 64/100
1/1 [==============================] - 0s 16us/step - loss: 0.7914
1/1 [==============================] - 0s 134ms/step - loss: 0.7914 - val_loss: 0.7293
Epoch 65/100
1/1 [==============================] - 0s 15us/step - loss: 0.7913
1/1 [==============================] - 0s 141ms/step - loss: 0.7913 - val_loss: 0.7289
Epoch 66/100
1/1 [==============================] - 0s 16us/step - loss: 0.7913
1/1 [==============================] - 0s 135ms/step - loss: 0.7913 - val_loss: 0.7286
Epoch 67/100
1/1 [==============================] - 0s 12us/step - loss: 0.7912
1/1 [==============================] - 0s 131ms/step - loss: 0.7912 - val_loss: 0.7283
Epoch 68/100
1/1 [==============================] - 0s 16us/step - loss: 0.7912
1/1 [==============================] - 0s 134ms/step - loss: 0.7912 - val_loss: 0.7280
Epoch 69/100
1/1 [==============================] - 0s 16us/step - loss: 0.7912
1/1 [==============================] - 0s 134ms/step - loss: 0.7912 - val_loss: 0.7278
Epoch 70/100
1/1 [==============================] - 0s 16us/step - loss: 0.7911
1/1 [==============================] - 0s 134ms/step - loss: 0.7911 - val_loss: 0.7275
Epoch 71/100
1/1 [==============================] - 0s 17us/step - loss: 0.7911
1/1 [==============================] - 0s 135ms/step - loss: 0.7911 - val_loss: 0.7273
Epoch 72/100
1/1 [==============================] - 0s 16us/step - loss: 0.7911
1/1 [==============================] - 0s 156ms/step - loss: 0.7911 - val_loss: 0.7272
Epoch 73/100
1/1 [==============================] - 0s 14us/step - loss: 0.7911
1/1 [==============================] - 0s 138ms/step - loss: 0.7911 - val_loss: 0.7270
Epoch 74/100
1/1 [==============================] - 0s 11us/step - loss: 0.7911
1/1 [==============================] - 0s 134ms/step - loss: 0.7911 - val_loss: 0.7269
Epoch 75/100
1/1 [==============================] - 0s 21us/step - loss: 0.7911
1/1 [==============================] - 0s 145ms/step - loss: 0.7911 - val_loss: 0.7268
Epoch 76/100
1/1 [==============================] - 0s 17us/step - loss: 0.7911
1/1 [==============================] - 0s 140ms/step - loss: 0.7911 - val_loss: 0.7267
Epoch 77/100
1/1 [==============================] - 0s 17us/step - loss: 0.7911
1/1 [==============================] - 0s 138ms/step - loss: 0.7911 - val_loss: 0.7266
Epoch 78/100
1/1 [==============================] - 0s 16us/step - loss: 0.7911
1/1 [==============================] - 0s 137ms/step - loss: 0.7911 - val_loss: 0.7265
Epoch 79/100
1/1 [==============================] - 0s 14us/step - loss: 0.7911
1/1 [==============================] - 0s 138ms/step - loss: 0.7911 - val_loss: 0.7264
Epoch 80/100
1/1 [==============================] - 0s 16us/step - loss: 0.7911
1/1 [==============================] - 0s 133ms/step - loss: 0.7911 - val_loss: 0.7263
Epoch 81/100
1/1 [==============================] - 0s 12us/step - loss: 0.7911
1/1 [==============================] - 0s 134ms/step - loss: 0.7911 - val_loss: 0.7263
Epoch 82/100
1/1 [==============================] - 0s 14us/step - loss: 0.7911
1/1 [==============================] - 0s 136ms/step - loss: 0.7911 - val_loss: 0.7262
Epoch 83/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7261
Epoch 84/100
1/1 [==============================] - 0s 15us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7261
Epoch 85/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 143ms/step - loss: 0.7910 - val_loss: 0.7261
Epoch 86/100
1/1 [==============================] - 0s 19us/step - loss: 0.7910
1/1 [==============================] - 0s 139ms/step - loss: 0.7910 - val_loss: 0.7260
Epoch 87/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 137ms/step - loss: 0.7910 - val_loss: 0.7260
Epoch 88/100
1/1 [==============================] - 0s 32us/step - loss: 0.7910
1/1 [==============================] - 0s 132ms/step - loss: 0.7910 - val_loss: 0.7260
Epoch 89/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 133ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 90/100
1/1 [==============================] - 0s 14us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 91/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 92/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 134ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 93/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7259
Epoch 94/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 95/100
1/1 [==============================] - 0s 11us/step - loss: 0.7910
1/1 [==============================] - 0s 148ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 96/100
1/1 [==============================] - 0s 17us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 97/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 98/100
1/1 [==============================] - 0s 17us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 99/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 136ms/step - loss: 0.7910 - val_loss: 0.7258
Epoch 100/100
1/1 [==============================] - 0s 16us/step - loss: 0.7910
1/1 [==============================] - 0s 135ms/step - loss: 0.7910 - val_loss: 0.7258
predictions = model %>% predict(hitters_scale_train)
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: in user code:
/Users/luningm/Library/r-miniconda/envs/r-reticulate/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py:1147 predict_function *
outputs = self.distribute_strategy.run(
/Users/luningm/Library/r-miniconda/envs/r-reticulate/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:951 run **
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/Users/luningm/Library/r-miniconda/envs/r-reticulate/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:2290 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/Users/luningm/Library/r-miniconda/envs/r-reticulate/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:2649 _call_for_each_replica
return fn(*args, **kwargs)
/Users/luningm/Library/r-miniconda/envs/r-reticulate/lib/python3.6/site-packages/tensorflow/python/keras/engine/train
rmse(exp(predictions), hitters_test_labels)
[1] 427.3493
hitters_scale_train$Salary = hitters_train_labels
train.control = trainControl(method = "cv", number = 10)
step.model = train(Salary ~ ., data = regression_df, method = "leapForward", trControl = train.control)
step.model
Linear Regression with Forward Selection
262 samples
19 predictor
No pre-processing
Resampling: Cross-Validated (10 fold)
Summary of sample sizes: 237, 236, 238, 235, 237, 236, ...
Resampling results across tuning parameters:
nvmax RMSE Rsquared MAE
2 174.3334 0.03794978 83.17090
3 177.1809 0.03520991 87.31275
4 178.9360 0.05608945 89.25318
RMSE was used to select the optimal model using the smallest value.
The final value used for the model was nvmax = 2.
The neural network model did considerably worse than the stepwise linear regression model.